WO2020078463A1 - 驾驶环境智能调整及驾驶员注册方法和装置、车辆、设备 - Google Patents

驾驶环境智能调整及驾驶员注册方法和装置、车辆、设备 Download PDF

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Publication number
WO2020078463A1
WO2020078463A1 PCT/CN2019/111930 CN2019111930W WO2020078463A1 WO 2020078463 A1 WO2020078463 A1 WO 2020078463A1 CN 2019111930 W CN2019111930 W CN 2019111930W WO 2020078463 A1 WO2020078463 A1 WO 2020078463A1
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WIPO (PCT)
Prior art keywords
information
driver
driving environment
seat
face
Prior art date
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PCT/CN2019/111930
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English (en)
French (fr)
Inventor
梁冠华
易成名
韦阳
Original Assignee
上海商汤智能科技有限公司
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Application filed by 上海商汤智能科技有限公司 filed Critical 上海商汤智能科技有限公司
Priority to KR1020207014677A priority Critical patent/KR102391380B1/ko
Priority to EP19872497.3A priority patent/EP3868610A4/en
Priority to SG11202004947YA priority patent/SG11202004947YA/en
Priority to JP2020528221A priority patent/JP2021504214A/ja
Publication of WO2020078463A1 publication Critical patent/WO2020078463A1/zh
Priority to US16/882,869 priority patent/US20200324784A1/en
Priority to JP2022134359A priority patent/JP2022180375A/ja

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/0098—Details of control systems ensuring comfort, safety or stability not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
    • B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
    • B60R16/037—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for occupant comfort, e.g. for automatic adjustment of appliances according to personal settings, e.g. seats, mirrors, steering wheel
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R11/00—Arrangements for holding or mounting articles, not otherwise provided for
    • B60R11/04—Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/01—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles operating on vehicle systems or fittings, e.g. on doors, seats or windscreens
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/20—Means to switch the anti-theft system on or off
    • B60R25/25—Means to switch the anti-theft system on or off using biometry
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/30—Detection related to theft or to other events relevant to anti-theft systems
    • B60R25/305—Detection related to theft or to other events relevant to anti-theft systems using a camera
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/30—Detection related to theft or to other events relevant to anti-theft systems
    • B60R25/34—Detection related to theft or to other events relevant to anti-theft systems of conditions of vehicle components, e.g. of windows, door locks or gear selectors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
    • G—PHYSICS
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    • G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
    • G06V20/597—Recognising the driver's state or behaviour, e.g. attention or drowsiness
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G—PHYSICS
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    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/168—Feature extraction; Face representation
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    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks

Definitions

  • This application relates to computer vision technology, in particular to a method and device, vehicle, and equipment for intelligent adjustment of the driving environment and driver registration.
  • the prior art proposes to personalize the driver settings to provide the driver with a more comfortable driving environment.
  • the embodiments of the present application provide a technical solution for intelligent adjustment of a driving environment and driver registration.
  • a method for intelligently adjusting a driving environment includes:
  • the driving environment personality corresponding to the registered face feature corresponding to the face feature is determined according to the correspondence between the pre-stored registered face feature and the driving environment personalized setting information Setting information;
  • a driver registration method includes:
  • a driving environment intelligent adjustment device includes:
  • the feature extraction unit is used to extract the facial features of the driver's image collected by the on-board camera;
  • a facial feature authentication unit configured to authenticate the extracted facial features based on at least one registered facial feature stored in advance
  • the environment information acquisition unit is configured to determine the registered face corresponding to the face feature according to the correspondence between the registered face feature stored in advance and the personalized setting information of the driving environment in response to the face feature authentication Personalized setting information of driving environment corresponding to features;
  • the information processing unit is configured to send the personalized driving environment setting information to the vehicle provided with the vehicle-mounted camera, or control the vehicle to adjust the driving environment accordingly according to the personalized driving environment setting information.
  • a driver registration device includes:
  • Image acquisition module used to acquire the driver's image
  • a facial feature extraction module to extract facial features of the image
  • Parameter information acquisition module to obtain the setting information of driving environment parameters
  • the registration information storage module stores the extracted facial features as registered facial features, stores the setting information of the driving environment parameters as the personalized driving environment setting information of the registered facial features, establishes and stores the registered facial features Correspondence between the personalized setting information of the driving environment.
  • a vehicle including: the driving environment intelligent adjustment device as described above or the driver registration device as described above.
  • an electronic device including a processor, the processor including the driving environment intelligent adjustment device described above or the driver registration device described above .
  • an electronic device including: a memory for storing executable instructions;
  • a processor for communicating with the memory to execute the executable instructions to complete any of the driving environment intelligent adjustment methods described above or the driver registration method described above.
  • a computer storage medium for storing computer readable instructions, characterized in that, when the instructions are executed, the intelligent driving environment adjustment method described in any one of the above is executed Or the operation of the driver registration method as described above.
  • a computer program product including computer readable code, characterized in that, when the computer readable code runs on a device, the processor in the device executes In order to implement the driving environment intelligent adjustment method as described above or the driver registration method as described above as an instruction.
  • FIG. 1 is a schematic flowchart of a driving environment intelligent adjustment method provided by an embodiment of the present application.
  • FIG. 2 is another schematic flowchart of a driving environment intelligent adjustment method provided by an embodiment of the present application.
  • FIG. 3 is a schematic diagram of setting personalized driving environment setting information in an alternative example of an intelligent driving environment adjustment method provided by an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of setting a driving environment parameter in another embodiment of the intelligent driving environment adjustment method provided by an embodiment of the present application.
  • Fig. 5 is a reference diagram of the position of the vehicle coordinate system and the camera coordinate system.
  • FIG. 6 is a schematic result diagram of the translation of the camera coordinate system space point to the vehicle-machine coordinate system.
  • FIG. 7 is a schematic diagram of the seat adjustment simplified camera coordinate system and the vehicle-machine coordinate system.
  • FIG. 8 is a schematic diagram of the rotation of the coordinate point (x_1, z_1) under the camera coordinate system to the coordinate point (x_0, z_0) under the vehicle-machine coordinate system.
  • FIG. 9 is a schematic flowchart of a part of an optional example of intelligent adjustment of a driving environment provided by an embodiment of the present application.
  • FIG. 10 is a system schematic diagram of another optional example of the intelligent driving environment adjustment method provided by the embodiment of the present application.
  • FIG. 11 is a schematic structural diagram of a driving environment intelligent adjustment device according to an embodiment of the present application.
  • FIG. 12 is a schematic flowchart of a driver registration method provided by an embodiment of the present application.
  • FIG. 13 is a schematic structural diagram of a driver registration device provided by an embodiment of the present application.
  • FIG. 14 is a schematic structural diagram of an electronic device suitable for implementing a terminal device or a server according to an embodiment of the present application.
  • the embodiments of the present application can be applied to a computer system / server, which can operate together with many other general-purpose or special-purpose computing system environments or configurations.
  • Examples of well-known computing systems, environments, and / or configurations suitable for use with computer systems / servers include, but are not limited to: in-vehicle devices, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop Equipment, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the above systems, etc.
  • the computer system / server may be described in the general context of computer system executable instructions (such as program modules) executed by the computer system.
  • program modules may include routines, programs, target programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types.
  • the computer system / server can be implemented in a distributed cloud computing environment. In a distributed cloud computing environment, tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules may be located on local or remote computing system storage media including storage devices.
  • FIG. 1 is a schematic flowchart of a driving environment intelligent adjustment method provided by an embodiment of the present application.
  • the method can be performed by any electronic device, such as a terminal device, a server, a mobile device, an in-vehicle device, etc.
  • the method in this embodiment includes:
  • Step 110 Extract the facial features of the driver's image collected by the on-board camera.
  • the driver's image can be obtained through a car camera, which can be a camera device installed in the vehicle interior (such as the driving area, rearview mirror, or center console, etc.) or outside the vehicle (such as a car pillar) Acquisition, and feature extraction can be achieved based on neural network, through the neural network feature extraction of the driver's image to obtain the driver's face features, you can also extract the face features of the driver's image by other means, this application is implemented For example, it does not limit the specific methods of acquiring images of drivers and acquiring facial features.
  • the neural networks in the embodiments of the present application may be a multi-layer neural network (ie, deep neural network), wherein the neural network may be a multi-layer convolutional neural network, for example, LeNet, AlexNet , GoogLeNet, VGG, ResNet and other arbitrary neural network models.
  • Each neural network may use a neural network of the same type and structure, or a neural network of a different type and / or structure. The embodiments of the present application do not limit this.
  • this step 110 may be executed by the processor invoking the corresponding instruction stored in the memory, or may be executed by the feature extraction unit 1101 executed by the processor.
  • Step 120 Authenticate the extracted facial features based on at least one registered facial feature stored in advance.
  • the similarity between the facial features of the driver ’s image and the registered facial features can be identified to determine whether the driver can pass the authentication; when the driver ’s facial features are similar to a registered facial feature
  • the face feature can be considered to be authenticated; optionally, the registered face feature can be received through the mobile application or the vehicle machine, and its registration process It also includes obtaining personalized setting information of the driving environment corresponding to the features of the registered face.
  • a vehicle may include one or more registered facial features.
  • the registered facial features may be stored locally on the mobile application, on the vehicle-machine side, or in a cloud database to ensure that the registered facial features can be obtained during authentication Features, optionally, while storing the registered face features, it can also store the face image of the registered driver, storing the registered face features saves storage space compared to storing the face images, and the extracted face features are recognized by the computer
  • the computer expression used to represent the facial features has been desensitized relative to the facial image and processed based on the facial features, which is convenient for protecting the driver ’s physiological privacy information from being leaked.
  • this step 120 may be executed by the processor invoking the corresponding instruction stored in the memory, or may also be executed by the facial feature authentication unit 1102 executed by the processor.
  • Step 130 in response to the face feature authentication being passed, determining the personalization of the driving environment corresponding to the registered face feature corresponding to the face feature according to the correspondence between the pre-stored registered face feature and the personalized setting information of the driving environment Set the information.
  • the registered registered face features not only save the registered face features and the personalized driving environment setting information, but also save the correspondence between the registered face features and the driving environment personalized setting information; therefore, the face features After the authentication is passed, the personalized setting information of the driving environment corresponding to the registered facial features can be obtained through the correspondence relationship, such as: interior lights, interior air conditioning temperature, interior music style, etc.
  • this step 130 may be executed by the processor invoking the corresponding instruction stored in the memory, or may be executed by the environment information obtaining unit 1103 executed by the processor.
  • Step 140 Send personalized setting information of the driving environment to the vehicle provided with the vehicle-mounted camera, or control the vehicle to adjust the driving environment accordingly according to the personalized setting information of the driving environment.
  • the vehicle cannot be directly set, and the personalized setting information of the driving environment can be sent to the vehicle
  • the settings are achieved through the on-board equipment; when the personalized setting information of the driving environment is obtained through the on-board equipment set on the vehicle end, the vehicle will be adjusted accordingly according to the information; if the driver wants to change these settings during use Content, you can re-set the personalized driving environment setting information through the registration terminal (such as the mobile application or the vehicle terminal).
  • the vehicle-side terminal directly accepts the driving environment personalized setting information sent by the registration terminal through the receiving cloud server. It can realize real-time personalized setting information adjustment of driving environment.
  • this step 140 may be executed by the processor invoking the corresponding instruction stored in the memory, or may be executed by the information processing unit 1104 executed by the processor.
  • This application is based on facial features as registration and / or personalized driving environment intelligent configuration
  • the authentication method improves the accuracy of the authentication and the safety of the vehicle, and the realization of intelligent personalized configuration based on the comparison of facial features is also conducive to protecting the driver's privacy and improving the driving comfort, intelligence and user experience.
  • the personalized setting information of the driving environment may include, but is not limited to, at least one of the following: temperature information, lighting information, music style information, seat status information, sound setting information, and the like.
  • one or more items such as temperature information, lighting information, music style information, seat status information, sound setting information, etc. in the vehicle can be set.
  • Other information that affects the environment also belongs to the personalized driving environment setting information that can be set in this application.
  • it further includes:
  • a registration application reminder message or authentication failing prompt message is issued.
  • the requested device may issue a notification message that the authentication fails, indicating that the driver has not Registering the vehicle, the personalized setting information of the driving environment cannot be obtained; or, the requested device can issue a registration application prompt message to prompt the driver to register, and the driver can obtain the personalized setting information of the driving environment after completing the registration .
  • FIG. 2 is another schematic flowchart of a driving environment intelligent adjustment method provided by an embodiment of the present application. As shown in FIG. 2, the method of the embodiment of the present application includes:
  • Step 210 Extract the facial features of the driver's image collected by the on-board camera.
  • Step 210 in the embodiment of the present application is similar to step 110 in the above-mentioned embodiment, and the step can be understood by referring to the above-mentioned embodiment, which will not be repeated here.
  • Step 220 Obtain the driver's registered facial features, personalized driving environment setting information, and the correspondence between the two through the driver registration process.
  • step 210 can be executed before step 220, or step 220 can be executed before step 210.
  • driver registration is achieved by acquiring the driver ’s registered facial features, personalized driving environment setting information, and the correspondence between the two.
  • the driver registration in the embodiment of the present application is based on the registered facial features as the only recognition Information, which improves the accuracy of the identification of registered drivers and reduces the problem of forgery due to other information based on gender as identification information.
  • Step 230 Authenticate the extracted facial features based on at least one registered facial feature stored in advance.
  • Step 230 in the embodiment of the present application is similar to step 120 in the foregoing embodiment, and this step can be understood with reference to the foregoing embodiment, and details are not described herein again.
  • Step 240 in response to the authentication of the facial features, determining the personalization of the driving environment corresponding to the registered facial features corresponding to the facial features according to the correspondence between the pre-stored registered facial features and the personalized setting information of the driving environment Set the information.
  • Step 240 in this embodiment of the present application is similar to step 130 in the foregoing embodiment, and this step can be understood with reference to the foregoing embodiment, and details are not described herein again.
  • Step 250 Send personalized driving environment setting information to the vehicle provided with the onboard camera, or control the vehicle to adjust the driving environment accordingly according to the personalized driving environment setting information.
  • step 250 is similar to step 140 in the foregoing embodiment, and this step can be understood by referring to the foregoing embodiment, and details are not described herein again.
  • driver registration before performing facial feature authentication, driver registration is required, so that the vehicle acquires at least one registered facial feature to ensure that the facial feature can be authenticated after acquiring the driver's facial feature, optional
  • the driver registration process includes:
  • the image of the driver requesting registration can be obtained through the mobile application or the vehicle-machine side.
  • Both the mobile application and the vehicle-machine side are provided with cameras and other camera devices, and the driver's image is collected through the camera to perform human image manipulation.
  • Facial feature extraction to obtain facial features receive the driver's input of driving environment parameter setting information through the device, or extract the driving parameter setting information set in the vehicle from the vehicle side; in order to ensure the personalization of registered facial features and driving environment There is a one-to-one correspondence between the setting information.
  • the correspondence between the registered face features and the personalized driving environment setting information is also saved; when you need to obtain the personalized driving environment setting information later, you only need to match the face features Obtaining the corresponding personalized driving environment setting information through the correspondence relationship does not require a complicated process, and realizes the intelligent personalized configuration based on the facial features, and realizes the fast driving environment personalized setting information acquisition on the premise of protecting the driver's privacy.
  • FIG. 3 is a schematic diagram of setting personalized driving environment setting information in an alternative example of an intelligent driving environment adjustment method provided by an embodiment of the present application.
  • the personalized driving environment setting information set on the mobile application uses the registered facial features as the only recognition method; where the personalized driving environment setting information includes temperature ( ACTemperature), Ambient Light (Color) and Music Style (Music Style), the mobile application can also display the face image of the registered driver, and can also set the name (Name) for the registered driver.
  • the personalized driving environment setting information includes temperature ( ACTemperature), Ambient Light (Color) and Music Style (Music Style)
  • the mobile application can also display the face image of the registered driver, and can also set the name (Name) for the registered driver.
  • the registration storage unit where the environment personalized setting information is located can be stored in the register of the mobile application; Name can be modified, and after the registration is completed, the Name can also be modified, for example: when the registration is A, after the registration is modified to B;
  • the personalized setting information of the above driving environment can be set, changed, and saved.
  • the facial features need to be authenticated. Only after the authentication is passed can the operation be performed.
  • obtaining an image of the driver including:
  • the driver's image can be obtained through the mobile application and / or the on-board camera, that is, the driver can choose a convenient port by himself when requesting registration, and can use the mobile application (such as mobile phone, tablet computer, etc.) ) Registration; you can also register through the car machine side.
  • the driver's image is collected through the car camera.
  • the car camera can be set in front of the driver's seat, corresponding to the personalized setting information of the driving environment on the car machine side.
  • the collection can be obtained by the driver through the interactive device input of the car machine or by reading the vehicle setting data through the on-board device.
  • obtaining the driver's image through the mobile application includes:
  • the driver's image is acquired through the camera device set on the mobile application.
  • the driver's image is obtained through the mobile application terminal.
  • the mobile application terminal referred to in this embodiment of the present application includes but is not limited to: mobile phones, tablet computers and other devices with camera and storage functions; since the mobile application terminal has camera and storage functions,
  • the way to obtain the driver image can be obtained by selecting the driver image from the images stored in the mobile application, or by acquiring the driver image through the camera of the mobile application.
  • obtaining setting information of driving environment parameters including:
  • the driving environment parameters include, but are not limited to: the interior temperature, lighting, music style, seat status, and sound settings Parameters related to the driving environment. These environment parameters can be set according to the driver's input through the device, for example: adjust the temperature in the car to 22 degrees through the mobile application, and set the light color to warm yellow.
  • the setting information of the driving environment parameters in the vehicle may be collected by the on-board equipment in addition to the above-mentioned reception through the mobile application terminal and / or the on-board equipment.
  • the two methods can be combined or used separately.
  • obtaining setting information of driving environment parameters including:
  • the personalized setting information of the driving environment corresponding to the registered facial features is updated based on the collected setting information of the driving environment parameters.
  • the driver may not be in the car when setting through the device (mobile application, etc.), and does not know much about the environment inside and outside the car. Therefore, the information set may be inaccurate, and there is also a
  • the internal and external environment of the car has changed during the driving process.
  • the previously set information is no longer suitable for the current environment. For example: due to time changes during driving, the external environment becomes dark. To facilitate driving, you need to change the lighting information at this time;
  • the driver can directly set the driving environment parameters in the car after facial feature authentication, and after setting, collect the setting information of the driving environment parameters through the on-board equipment. Based on the setting information of the driving environment parameters, the personalized setting information of the driving environment corresponding to the registered facial features is updated to make the personalized setting information of the driving environment more in line with the needs of the driver.
  • the method in the embodiment of the present application further includes: performing at least one of the following operations on the stored personalized driving environment setting information according to the received management instruction: deleting, editing, permission setting, and the like.
  • an administrator with authority can operate the personalized setting information of the driving environment through management instructions, for example: the owner deletes the registered facial features and personalized setting information of the driving environment of a driver in the vehicle, Or the owner can limit the authority of a certain driver to only adjust the seat status, etc .; through the operation of personalized setting information on the driving environment, personalized authority management is realized.
  • the correspondence between the registered facial features and the personalized setting information of the driving environment is stored in at least one of the following locations: mobile application, server, vehicle-mounted device, and so on.
  • the information and relationships of the registered facial features can be stored in the mobile application, server, or vehicle-mounted device, etc.
  • the vehicle and mobile applications communicate with each other, and the vehicle obtains driving You can download the corresponding information from the mobile application for authentication, or transfer the facial features to the mobile application for authentication.
  • the mobile application sends the personalized driving environment setting information to the vehicle; when it is stored in In the vehicle-mounted device, the vehicle-end does not need to communicate with the outside world, and directly authenticates the driver's facial features obtained by the vehicle camera and the registered facial features stored in the vehicle-mounted device; when stored in the server, the server and the vehicle-mounted device Communicate with each other.
  • the vehicle can download the corresponding information from the server for authentication, or upload the facial features to the server for authentication.
  • the server sends the personalized driving environment setting information to the vehicle.
  • sending the personalized driving environment setting information to the vehicle provided with the on-board camera in step 140 in the foregoing embodiment includes:
  • the personalized setting information of the driving environment is sent to the vehicle provided with the on-board camera through a server or mobile application that communicates with the vehicle.
  • the server or mobile application is used as the authentication subject, and face feature authentication is implemented in the server or mobile application.
  • the personalized driving environment setting information stored in the server or mobile application is sent to the car.
  • the setting is completed on the vehicle side, and is not subject to the management control of the server or mobile application side.
  • the server or mobile application side only completes the driving environment personalized setting information and sends it to the vehicle side.
  • the corresponding adjustment of the driving environment of the vehicle provided with the on-board camera according to the driving environment personalized setting information includes:
  • the driving environment of the vehicle with the on-board camera is adjusted accordingly.
  • the embodiment of the present application implements the authentication of the face of the vehicle as the main body of authentication, and there are two possibilities at this time: the registered face features and the personalized setting information of the driving environment are stored on the side of the vehicle, or Registered face features and driving environment personalized setting information are stored in the mobile application or server; when the driving environment personalized setting information is stored in the vehicle, the in-vehicle device directly calls the driving environment personalized setting information to set the vehicle accordingly, while driving When the personalized environment setting information is stored in the mobile application or server, the personalized driving environment setting information corresponding to the registered facial features needs to be downloaded from the mobile application or server, and the vehicle is set accordingly based on the personalized driving environment setting information .
  • FIG. 4 is a schematic flowchart of setting a driving environment parameter in another embodiment of the intelligent driving environment adjustment method provided by an embodiment of the present application.
  • the setting information of the driving environment parameters in this embodiment includes seat state information; obtaining the setting information of the driving environment parameters, as shown in FIG. 4, includes:
  • Step 410 Detect the driver's image to obtain the detection result.
  • the image of the driver entering the vehicle is collected, and the detected image of the driver is used for detection.
  • the detection may be implemented based on a neural network or other methods.
  • the embodiments of the present application do not limit the specific method of detecting the image of the driver.
  • Step 420 Determine the driver's body shape-related information and / or face height information according to the detection result.
  • body-type related information may include but not limited to: race, gender and other information related to the driver's ride (such as: fatness and thinness, leg length information, skeleton size information , Hand length information, etc.) influential information.
  • detecting face reference points based on a key point detection network to obtain face reference points to determine face height information neural network based on attribute detection performing attribute detection on driver images to determine body type-related information, or
  • the body shape-related information of the driver can be determined through the results of human or face detection, or the body shape-related information can be obtained directly by classification neural network detection, for example: through the gender recognized by the face, the driver ’s skeleton size information can be obtained, female 'S skeleton is too small, while the male skeleton is too large.
  • Step 430 Determine the driver's seat state information based on body shape-related information and / or face height information.
  • the comfortable sitting posture of the human body is not only related to the height of the sitting posture, but also to the body shape.
  • the embodiments of the present application obtain information about the body shape and / or face height of the driver to obtain The adjustment information of the seat is determined.
  • the seat adjusted according to the adjustment information of the seat in the embodiment of the present application provides the driver with a more suitable sitting posture and improves the driver's comfort in use.
  • the detection result includes the coordinates of the face reference point
  • Step 410 includes performing face reference point detection on the driver's image to obtain the driver's face reference point coordinates in the camera coordinate system.
  • the face reference point can be any point on the face, it can be a key point on the face, or it can be another position on the face, because the driver ’s field of vision plays an important role during the driving of the vehicle; For the driver, ensuring the driver ’s binocular height during driving can improve driving safety. Therefore, the face reference point can be set to a point related to the eyes, for example: at least one key point to determine the position of the eyes, or Eyebrow position points, etc .; the embodiments of the present application do not limit the number and position of specific face reference points, as long as the face height can be determined.
  • the face reference point includes at least one face key point and / or at least one other face position point;
  • step 410 includes: performing face reference point detection on the driver's image to obtain the driver's on-camera The coordinates of at least one face key point in the coordinate system;
  • the position of key points on the face can be determined through the neural network, for example: one or more of 21 key points on the face, 106 key points on the face, and 240 key points on the face, through different networks
  • the number of obtained key points is different, which can include the key points of facial features, or can also include the key points of the face contour.
  • the key points are different in density and density, which leads to the difference in the number of key points obtained; one of the obtained key points Or multiple reference points for the face only need to select different parts according to specific conditions.
  • the embodiments of the present application do not limit the position and number of key points of the face.
  • the reference point may also be other position points of the face on the face image determined based on the detection results of the key points of the face.
  • These other position points of the face may not be key points, that is, any position points on the face, However, its position can be determined according to the key points of the face, for example, the position of the eyebrow center can be determined based on the key points of the eyes and the key points of the eyebrows.
  • Step 420 includes: converting the coordinates of the face reference point from the camera coordinate system to the vehicle-machine coordinate system;
  • the face height information of the driver is determined based on the coordinates of the face reference point in the vehicle-machine coordinate system.
  • the face reference point since the face reference point is obtained from the image collected by the camera, the face reference point corresponds to the camera coordinate system, and when determining the seat information, it needs to be determined under the vehicle-machine coordinate system. Therefore, The face reference point needs to be converted from the camera coordinate system to the vehicle coordinate system.
  • the coordinate system conversion method commonly used in the prior art may be used to convert the eyebrow position coordinates from the camera coordinate system to the vehicle machine coordinate system, for example:
  • FIG. 5 is a reference map of the position of the vehicle machine coordinate system and the camera coordinate system, Among them, in the vehicle coordinate system: the y axis is the front wheel axle, the x axis is parallel to the upper left edge, and the z axis is perpendicular to the ground and downward.
  • FIG. 6 is a schematic result diagram of the translation of the camera coordinate system space point to the vehicle-machine coordinate system. As shown in Fig. 6: The origin Oc of the camera coordinate system is translated to the origin O of the vehicle coordinate system.
  • Oc is (Xwc, Ywc, Zwc) in the vehicle coordinate system, and Oc is (0,0,0) in the camera coordinate system, and it is translated to the origin O (0,0,0) of the vehicle coordinate system.
  • FIG. 7 is a schematic diagram of the seat adjustment simplified camera coordinate system and the vehicle-machine coordinate system.
  • the X axis in the vehicle coordinate system is not adjusted, then the coordinate points in the camera coordinate system are converted to the vehicle coordinate system and simplified to the two-dimensional coordinate system.
  • FIG. 8 is a schematic diagram of the coordinate point (x 1 , z 1 ) in the camera coordinate system rotating to the coordinate point (x 0 , z 0 ) in the vehicle coordinate system.
  • the coordinate point of the driver's head is (y 1 , z 1 ) detected under the camera coordinate system, and after the rotation angle ⁇ , that is, the installation angle of the camera, the coordinate point (x 0 , z 0 ).
  • the coordinate point under the camera coordinate system can be rotated and translated to the coordinates under the vehicle coordinate system as follows:
  • the face height information of the driver in the vehicle can be determined, that is, the relative position relationship between the face height and the seat can be determined, and the desired seat state information corresponding to the face height information can be obtained.
  • the body type-related information includes race information and / or gender information
  • Step 410 includes: inputting the image of the driver into the neural network for attribute detection to perform attribute detection, and obtaining the attribute detection result output by the neural network.
  • an attribute detection is implemented through a neural network, and the attribute detection result includes driver's race information and / or gender information;
  • the neural network may be a classification network including at least one branch, In the case of including one branch, classify racial information or gender information, in the case of including two branches, classify racial information and gender information; determine the racial and gender classification of the driver.
  • Step 420 includes: obtaining ethnic information and / or gender information of the driver corresponding to the image based on the attribute detection result.
  • step 430 includes:
  • the driver's desired seat state is determined, and the desired seat state is used as the driver's seat state information.
  • the seat adjustment conversion relationship may include, but is not limited to, a conversion formula or a correspondence table, etc.
  • the conversion formula may input body shape and / or face height into the formula to obtain data corresponding to the desired state of the seat, and the correspondence table may directly The data corresponding to the desired state of the seat is obtained based on a look-up table of body shape and / or face height.
  • the corresponding relationship table may be obtained through big data statistics, or obtained in other ways. The embodiment of the present application does not limit the specific way of obtaining the corresponding relationship table.
  • the desired state of the seat is also different, and multiple sets of corresponding formulas can be combined for different genders and races, such as: For the yellow race + male, for a seat adjustment formula, each dimension of the eyebrow coordinates (x, y, z) and backrest adjustment angle entered in each formula corresponds to a cubic unary function, for example:
  • the final calculated seat expectation state (x out , y out ) can be determined based on the coordinates of the eyebrow coordinates in the x-axis, y-axis, and z-axis directions , Z out , angle out ) through the final motor adjustment allocation formula to obtain the adjustment amount of 4 motors;
  • x out represents the front and rear position information of the seat
  • y out represents the seat cushion tilt angle information
  • z out represents the up and down of the seat Position information
  • angle out represents information about the reclining angle of the backrest chair;
  • a 4 , b 4 , c 4 , and d 4 are constants obtained through many experiments.
  • the final calculated seat expectation state (x out , y out , z out , angle out ) may also be determined based on the coordinates of the eyebrow coordinates in the z-axis direction (ie, the height of the eyebrows). Based on the following formula:
  • x out represents the front and rear position information of the seat
  • y out represents the seat cushion tilt angle information
  • z out represents the seat up and down position information
  • angle out represents the backrest seat tilt angle information
  • step 430 includes:
  • Step 901 Obtain a preset first seat adjustment conversion relationship related to face height.
  • the seat adjustment conversion relationship may include, but is not limited to, a conversion formula or a correspondence table, etc.
  • the conversion formula may input the face height into the formula to obtain data corresponding to the desired state of the seat, and the correspondence table may be directly based on the face height Look up the table to obtain the data corresponding to the desired state of the seat.
  • the correspondence table can be obtained through big data statistics, or obtained in other ways. The embodiment itself does not limit the specific way to obtain the correspondence table.
  • Step 902 based on the face height information and the first seat adjustment conversion relationship, determine a desired state of the first seat corresponding to the driver.
  • Step 903 Obtain a preset second seat adjustment conversion relationship related to body shape-related information.
  • the embodying related information corresponds to the second seat adjustment conversion relationship, which is different from the first seat adjustment conversion relationship, and its form may include but is not limited to a conversion formula or correspondence
  • the relationship table and the like can determine the second seat desired state through the second seat adjustment conversion relationship in combination with the body shape-related information and the first seat desired state.
  • Step 904 Determine the second seat desired state based on the body type-related information, the second seat adjustment conversion relationship, and the first seat desired state.
  • step 905 the second seat desired state is used as the driver's seat state information.
  • the seat state information is determined by combining body shape-related information and face height information, wherein the number of classifications obtained by combining race and gender in the body shape-related information is limited, and only needs to be determined as a combination, for example: male + yellow race, It is applicable to all drivers under this category.
  • the personalization is insufficient, but the information is easy to obtain; and the face height information is more personalized, and the adjustment information corresponding to different drivers may be different. Therefore, this embodiment achieves Information combined with personalized information improves the accuracy of seat status information.
  • the state information of the seat includes but is not limited to at least one of the following information: the target value of the seat adjustment parameter, the up and down position information of the seat, the front and rear position information of the seat, the left and right position information of the seat, the reclining seat reclining The position information of the angle, the position information of the inclination angle of the seat cushion.
  • the seat needs to be adjusted in multiple directions.
  • the seat reclining angle information and the seat reclining angle information are also included. For example: directly outputting the target values of various adjustment parameters such as up, down, left, right, and back to which the seat is finally adjusted, and how to adjust the target value can be processed by a motor or other equipment.
  • FIG. 10 is a system schematic diagram of another optional example of the intelligent driving environment adjustment method provided by the embodiment of the present application.
  • Figure 10 is a schematic diagram of the software system.
  • the system is divided into three parts: mobile application, cloud server and vehicle-side controller.
  • the data between the three parts are transmitted through the network; mobile application installation On mobile devices such as mobile phones or tablets, face registration and personalized settings of the driver ’s driving environment can be set, and the data can be transmitted to the cloud server;
  • the vehicle-side controller is installed on the vehicle and can perform interior lighting Color, temperature, music playback and seat control, and use the camera to upload the face information required by the driver to the cloud server;
  • the cloud server uses a database to access the data in the system; the specific implementation plan can be based on Adjust the actual application scenario.
  • FIG. 11 is a schematic structural diagram of a driving environment intelligent adjustment device according to an embodiment of the present application.
  • the device of this embodiment may be used to implement the above-mentioned embodiments of the method for intelligently adjusting the driving environment of the present application.
  • the device of this embodiment includes:
  • the feature extraction unit 1101 is used to extract the facial features of the driver's image collected by the on-board camera.
  • the face feature authentication unit 1102 is configured to authenticate the extracted face features based on at least one registered face feature stored in advance.
  • the environment information obtaining unit 1103 is configured to determine the correspondence of the registered face feature corresponding to the face feature according to the correspondence between the registered face feature stored in advance and the personalized setting information of the driving environment in response to the face feature authentication Personalized settings information for your driving environment.
  • the information processing unit 1104 is configured to send personalized driving environment setting information to a vehicle provided with an on-board camera, or control the vehicle to adjust the driving environment accordingly according to the personalized driving environment setting information.
  • the present application is based on facial features as a registration and / or authentication means for personalized intelligent configuration of the driving environment, which improves the accuracy of authentication and vehicle safety, and
  • the realization of intelligent personalized configuration based on face feature comparison is also conducive to protecting the driver's privacy, improving driving comfort, intelligence and user experience.
  • the personalized driving environment setting information includes at least one of the following: temperature information, lighting information, music style information, seat status information, and sound setting information.
  • the apparatus of the embodiments of the present application further includes:
  • the prompt information unit is configured to send a prompt message of registration application or a prompt message of authentication failure in response to the face feature authentication failure.
  • the device of the embodiment of the present application further includes: a driver registration unit, which is used to obtain the driver's registered facial features, personalized driving environment setting information, and both through the driver registration process Correspondence between.
  • a driver registration unit which is used to obtain the driver's registered facial features, personalized driving environment setting information, and both through the driver registration process Correspondence between.
  • the driver registration unit includes:
  • Image acquisition module used to acquire the driver's image
  • Face feature extraction module used to extract the face features of the image
  • Parameter information acquisition module used to obtain the setting information of driving environment parameters
  • the registration information storage module is used to store the extracted face features as registered face features, store the setting information of the driving environment parameters as the personalized setting information of the driving environment of the registered face features, establish and store the registered face features and driving Correspondence between environment personalized setting information.
  • the image acquisition module is used to acquire the driver's image through the mobile application terminal and / or the on-board camera.
  • the image acquisition module is configured to acquire the driver's image from at least one image stored on the mobile application, or acquire the driver's image through the camera device provided on the mobile application.
  • the parameter information acquisition module is configured to receive the setting information of the driving environment parameters through the mobile application terminal and / or the vehicle-mounted device.
  • the parameter information acquisition module is used to collect the setting information of the driving environment parameters in the vehicle through the on-board device.
  • a parameter information acquisition module is used to collect the setting information of the driving environment parameters in the vehicle through on-board equipment; based on the collected setting information of the driving environment parameters, the driving corresponding to the registered facial features The environment personalized setting information is updated.
  • the driver registration unit further includes:
  • the information management module is used to perform at least one of the following operations on the stored personalized driving environment setting information according to the received management instruction: delete, edit, permission setting, etc.
  • the correspondence between the registered facial features and the personalized driving environment setting information is stored in at least one of the following locations: mobile application, server, vehicle-mounted device, and so on.
  • the information processing unit when the information processing unit sends the driving environment personalized setting information to the vehicle provided with the vehicle-mounted camera, the information processing unit is used to send the driving environment personalized setting to the vehicle provided with the vehicle-mounted camera through a server or a mobile application that communicates with the vehicle information.
  • the information processing unit controls the corresponding adjustment of the driving environment of the vehicle provided with the on-board camera according to the personalized setting information of the driving environment, the Adjust the driving environment accordingly.
  • the setting information of the driving environment parameters includes: seat state information;
  • the parameter information acquisition module is used to detect the driver's image to obtain the detection result; determine the driver's body-related information and / or face height information based on the detection result; based on the body-type related information and / or face height information, determine Driver's seat status information.
  • the detection result includes the coordinates of the face reference point
  • the parameter information acquisition module detects the driver's image and obtains the detection result, it is used to detect the face reference point of the driver's image to obtain the driver's face reference point coordinates in the camera coordinate system;
  • the parameter information acquisition module is used to convert the coordinates of the face reference point from the camera coordinate system to the vehicle-machine coordinate system when the detection result determines the face height information of the driver; it is determined based on the coordinates of the face reference point under the vehicle-machine coordinate system Driver's face height information.
  • the face reference point includes at least one face key point and / or at least one other face position point;
  • the parameter information obtaining module is used to detect the face reference point of the driver's image and obtain the face reference point coordinates of the driver in the camera coordinate system. At least one face key point coordinate in the camera coordinate system; and / or, determining at least one face other position point based on the at least one face key point coordinate.
  • the body type-related information includes race information and / or gender information
  • the parameter information acquisition module detects the driver's image and obtains the detection result, it is used to input the driver's image into the neural network for attribute detection to perform attribute detection to obtain the attribute detection result output by the neural network;
  • the parameter information acquisition module is used to obtain the driver's race information and / or gender information corresponding to the image based on the attribute detection result when determining the driver's body type-related information according to the detection result.
  • the parameter information acquisition module is used to obtain a preset seat adjustment related to body shape and / or face height Conversion relationship; based on the body type related information and / or face height information and the seat adjustment conversion relationship, the driver's desired seat state is determined, and the desired seat state is used as the driver's seat state information.
  • the parameter information acquisition module is used to obtain a preset first seat adjustment conversion relationship related to face height ; Based on the face height information and the first seat adjustment conversion relationship, determine the driver's corresponding first seat desired state; obtain the preset second seat adjustment conversion relationship related to body shape related information; based on body shape related information, The second seat adjusts the conversion relationship and the first seat desired state to determine the second seat desired state; the second seat desired state is used as the driver's seat state information.
  • the state information of the seat includes at least one of the following information: the target value of the seat adjustment parameter, the up and down position information of the seat, the front and rear position information of the seat, the left and right position information of the seat, the position of the reclining angle of the backrest chair Information, position information of the seat cushion tilt angle.
  • FIG. 12 is a schematic flowchart of a driver registration method provided by an embodiment of the present application.
  • the method can be performed by any electronic device, such as a terminal device, a server, a mobile device, an in-vehicle device, etc.
  • the method in this embodiment includes:
  • Step 1210 Acquire an image of the driver.
  • acquiring the image of the driver requesting registration can be achieved through the mobile application or the vehicle-machine side, and both the mobile application and the vehicle-machine side are provided with camera and other camera devices, and the driver's image is collected through the camera.
  • this step 1210 may be executed by the processor invoking the corresponding instruction stored in the memory, or may be executed by the image acquisition module 1301 executed by the processor.
  • Step 1220 extract the facial features of the image.
  • the image can be feature-extracted through a convolutional neural network to obtain facial features, and the facial features of the image can also be obtained based on other means.
  • the embodiments of the present application do not limit the specific means for obtaining facial features.
  • this step 1220 may be executed by the processor invoking the corresponding instruction stored in the memory, or may be executed by the face feature extraction module 1302 executed by the processor.
  • Step 1230 Obtain the setting information of the driving environment parameters.
  • acquiring the image of the driver requesting registration can be achieved through the mobile application or the vehicle-machine side, and both the mobile application and the vehicle-machine side are provided with camera and other camera devices, and the driver's image is collected through the camera.
  • this step 1230 may be executed by the processor invoking the corresponding instruction stored in the memory, or may be executed by the parameter information obtaining module 1303 executed by the processor.
  • Step 1240 Store the extracted facial features as registered facial features, store the setting information of the driving environment parameters as the personalized driving environment setting information of the registered facial features, establish and store the registered facial features and the personalized driving environment settings Correspondence between information.
  • this step 1230 may be executed by the processor invoking the corresponding instruction stored in the memory, or may be executed by the registration information storage module 1304 executed by the processor.
  • the correspondence between the registered facial features and the driving environment personalized setting information is also saved; the driving environment needs to be obtained in the subsequent When personalizing the setting information, you only need to match the facial features to get the corresponding personalized driving environment setting information through the corresponding relationship. No complicated process is needed.
  • the intelligent personalized configuration is implemented to protect the driver ’s privacy. Under the premise of achieving a fast driving environment personalized setting information acquisition.
  • the personalized setting information of the driving environment includes at least one of the following: temperature information, lighting information, music style information, seat status information, sound setting information, and the like.
  • the personalized driving environment setting information set in the embodiments of the present application can provide a more comfortable driving environment for the driver, which is more in line with the personal habits of the driver, that is, different drivers can be set for different drivers of the same vehicle, and more Personalization improves driving comfort.
  • one or more of the temperature information, lighting information, music style information, seat status information, audio setting information and other information in the vehicle can be set, in addition to the above list Those skilled in the art should understand that other information that has an impact on the driving environment also belongs to the personalized driving environment setting information that can be set in this application.
  • step 1210 includes:
  • the driver's image can be obtained through the mobile application and / or the on-board camera, that is, the driver can choose a convenient port by himself when requesting registration, and can use the mobile application (such as mobile phone, tablet computer, etc.) ) Registration; you can also register through the car machine side.
  • the driver's image is collected through the car camera.
  • the car camera can be set in front of the driver's seat, corresponding to the personalized setting information of the driving environment on the car machine side
  • the collection can be obtained by the driver through the interactive device input of the car machine or by reading the vehicle setting data through the on-board device.
  • obtaining the driver's image through the mobile application includes:
  • the driver's image is acquired through the camera device set on the mobile application.
  • the driver's image is obtained through the mobile application terminal.
  • the mobile application terminal referred to in this embodiment of the present application includes but is not limited to: mobile phones, tablet computers and other devices with camera and storage functions; since the mobile application terminal has camera and storage functions,
  • the way to obtain the driver image can be obtained by selecting the driver image from the images stored in the mobile application, or by acquiring the driver image through the camera of the mobile application.
  • step 1230 includes:
  • the driving environment parameters include, but are not limited to: the interior temperature, lighting, music style, seat status, and sound settings Parameters related to the driving environment. These environment parameters can be set according to the driver's input through the device, for example: adjust the temperature in the car to 22 degrees through the mobile application, and set the light color to warm yellow.
  • the setting information of the driving environment parameters in the vehicle may be collected by the on-board equipment in addition to the above-mentioned reception through the mobile application terminal and / or the on-board equipment.
  • the two methods can be combined or used separately.
  • step 1230 includes:
  • the personalized setting information of the driving environment corresponding to the registered facial features is updated based on the collected setting information of the driving environment parameters.
  • the driver may not be in the car when setting through the device (mobile application, etc.), and does not know much about the environment inside and outside the car. Therefore, the information set may be inaccurate, and there is also a
  • the internal and external environment of the car has changed during the driving process.
  • the previously set information is no longer suitable for the current environment. For example: due to time changes during driving, the external environment becomes dark. To facilitate driving, you need to change the lighting information at this time;
  • the driver can directly set the driving environment parameters in the car after facial feature authentication, and after setting, collect the setting information of the driving environment parameters through the on-board equipment. Based on the setting information of the driving environment parameters, the personalized setting information of the driving environment corresponding to the registered facial features is updated to obtain the personalized setting information of the driving environment more in line with the needs of the driver.
  • the method of the embodiments of the present application further includes:
  • an administrator with authority can operate the personalized setting information of the driving environment through management instructions, for example: the owner deletes the registered facial features and personalized setting information of the driving environment of a driver in the vehicle, Or the owner can limit the authority of a certain driver to only adjust the seat status, etc .; through the operation of personalized setting information on the driving environment, personalized authority management is realized.
  • the correspondence between the registered facial features and the personalized setting information of the driving environment is stored in at least one of the following locations: mobile application, server, vehicle-mounted device, and so on.
  • the information and relationships of the registered facial features can be stored in the mobile application, server, or vehicle-mounted device, etc.
  • the vehicle and mobile applications communicate with each other, and the vehicle obtains driving You can download the corresponding information from the mobile application for authentication, or transfer the facial features to the mobile application for authentication.
  • the mobile application sends the personalized driving environment setting information to the vehicle; when it is stored in In the vehicle-mounted device, the vehicle-end does not need to communicate with the outside world, and directly authenticates the driver's facial features obtained by the vehicle camera and the registered facial features stored in the vehicle-mounted device; when stored in the server, the server and the vehicle-mounted device are required Communicate with each other.
  • the vehicle can download the corresponding information from the server for authentication, or upload the facial features to the server for authentication.
  • the server sends the personalized driving environment setting information to the vehicle.
  • the setting information of the driving environment parameters includes: seat state information;
  • Step 1230 includes:
  • the driver's seat state information is determined.
  • the solution of this embodiment is the same as the solution in another embodiment of the intelligent driving environment adjustment method shown in FIG. 4 above. It can be considered that the descriptions in the embodiment described in FIG. 4 above are applicable to this embodiment. And will not be repeated here.
  • the detection result includes the coordinates of the face reference point
  • Detect the driver's image to obtain the detection result including: detecting the face reference point of the driver's image to obtain the driver's face reference point coordinates in the camera coordinate system;
  • the detection result determines the driver's face height information, including: converting the face reference point coordinates from the camera coordinate system to the vehicle-machine coordinate system; determining the driver's face height based on the face reference point coordinates in the vehicle-machine coordinate system information.
  • the solution of this embodiment is the same as the solution in the corresponding embodiment of the intelligent driving environment adjustment method described above. It can be considered that the descriptions in the corresponding embodiments of the intelligent driving environment adjustment method above are applicable to this embodiment, which can be understood by reference. No longer.
  • the face reference point includes at least one face key point and / or at least one other face position point;
  • the solution of this embodiment is the same as the solution in the corresponding embodiment of the intelligent driving environment adjustment method described above. It can be considered that the descriptions in the corresponding embodiments of the intelligent driving environment adjustment method described above are applicable to this embodiment. No longer.
  • the body type-related information includes race information and / or gender information
  • Test the driver's image to obtain the test results including:
  • determine the driver's body-related information including:
  • the race information and / or gender information of the driver corresponding to the image is obtained.
  • the solution of this embodiment is the same as the solution in the corresponding embodiment of the intelligent driving environment adjustment method described above. It can be considered that the descriptions in the corresponding embodiments of the intelligent driving environment adjustment method described above are applicable to this embodiment. No longer.
  • the driver's seat state information is determined, including:
  • the driver's desired seat state is determined, and the desired seat state is used as the driver's seat state information.
  • the solution of this embodiment is the same as the solution in the corresponding embodiment of the intelligent driving environment adjustment method described above. It can be considered that the descriptions in the corresponding embodiments of the intelligent driving environment adjustment method above are applicable to this embodiment, which can be understood by reference. No longer.
  • the driver's seat state information is determined, including:
  • the solution of this embodiment is the same as the solution in the corresponding embodiment of the intelligent driving environment adjustment method described above. It can be considered that the descriptions in the corresponding embodiments of the intelligent driving environment adjustment method described above are applicable to this embodiment. No longer.
  • the state information of the seat includes at least one of the following information: the target value of the seat adjustment parameter, the up and down position information of the seat, the front and rear position information of the seat, the left and right position information of the seat, the position of the reclining angle of the backrest chair Information, position information of the seat cushion tilt angle.
  • the solution of this embodiment is the same as the solution in the corresponding embodiment of the intelligent driving environment adjustment method described above. It can be considered that the descriptions in the corresponding embodiments of the intelligent driving environment adjustment method above are applicable to this embodiment, which can be understood by reference. No longer.
  • FIG. 13 is a schematic structural diagram of a driver registration device provided by an embodiment of the present application.
  • the device of this embodiment may be used to implement the above driver registration method embodiments of the present application. As shown in FIG. 13, the device of this embodiment includes:
  • the image acquisition module 1301 is used to acquire an image of the driver.
  • the facial feature extraction module 1302 extracts facial features of the image.
  • the parameter information obtaining module 1303 obtains setting information of driving environment parameters.
  • the registration information storage module 1304 stores the extracted facial features as registered facial features, stores the setting information of the driving environment parameters as the personalized driving environment setting information of the registered facial features, establishes and stores the registered facial features and the driving environment Correspondence between personalized settings information.
  • the correspondence between the registered facial features and the driving environment personalized setting information is also saved; the driving environment needs to be obtained in the subsequent When personalizing the setting information, you only need to match the facial features to get the corresponding personalized driving environment setting information through the corresponding relationship. No complicated process is needed.
  • the intelligent personalized configuration is implemented to protect the driver ’s privacy. Under the premise of achieving a fast driving environment personalized setting information acquisition.
  • the personalized setting information of the driving environment includes at least one of the following: temperature information, lighting information, music style information, seat status information, sound setting information, and the like.
  • the image acquisition module is used to acquire the driver's image through the mobile application terminal and / or the on-board camera.
  • the image acquisition module is configured to acquire the driver's image from at least one image stored on the mobile application, or acquire the driver's image through the camera device provided on the mobile application.
  • the parameter information acquisition module 1303 is configured to receive the setting information of the driving environment parameters through the mobile application terminal and / or the vehicle-mounted device.
  • the parameter information acquisition module 1303 is configured to collect the setting information of the driving environment parameters in the vehicle through the in-vehicle device.
  • the parameter information obtaining module 1303 is configured to collect the setting information of the driving environment parameters in the vehicle through the on-board device; update the personalized setting information of the driving environment corresponding to the registered facial features based on the collected setting information of the driving environment parameters operating.
  • the apparatus of the embodiments of the present application further includes:
  • the information management module is used to perform at least one of the following operations on the stored personalized driving environment setting information according to the received management instruction: delete, edit, permission setting, etc.
  • the correspondence between the registered facial features and the personalized driving environment setting information is stored in at least one of the following locations: mobile application, server, vehicle-mounted device, and so on.
  • the setting information of the driving environment parameters includes: seat state information;
  • the parameter information acquisition module is used to detect the driver's image to obtain the detection result; determine the driver's body-related information and / or face height information based on the detection result; based on the body-type related information and / or face height information, determine Driver's seat status information.
  • the detection result includes the coordinates of the face reference point
  • the parameter information acquisition module detects the driver's image and obtains the detection result, it is used to detect the face reference point of the driver's image to obtain the driver's face reference point coordinates in the camera coordinate system;
  • the parameter information acquisition module is used to convert the coordinates of the face reference point from the camera coordinate system to the vehicle-machine coordinate system when the detection result determines the face height information of the driver;
  • the face height information of the driver is determined based on the coordinates of the face reference point in the vehicle-machine coordinate system.
  • the face reference point includes at least one face key point and / or at least one other face position point;
  • the parameter information obtaining module is used to detect the face reference point of the driver's image and obtain the face reference point coordinates of the driver in the camera coordinate system. At least one face key point coordinate in the camera coordinate system; and / or, determining at least one face other position point based on the at least one face key point coordinate.
  • the body type-related information includes race information and / or gender information
  • the parameter information acquisition module detects the driver's image and obtains the detection result, it is used to input the driver's image into the neural network for attribute detection to perform attribute detection to obtain the attribute detection result output by the neural network;
  • the parameter information acquisition module is used to obtain the driver's race information and / or gender information corresponding to the image based on the attribute detection result when determining the driver's body type-related information according to the detection result.
  • the parameter information acquisition module is used to obtain a preset seat adjustment related to body shape and / or face height Conversion relationship; based on the body type related information and / or face height information and the seat adjustment conversion relationship, the driver's desired seat state is determined, and the desired seat state is used as the driver's seat state information.
  • the parameter information acquisition module is used to obtain a preset first seat adjustment conversion relationship related to face height; The relationship between the face height information and the first seat adjustment conversion to determine the driver ’s desired state of the first seat; obtain the preset second seat adjustment conversion relationship related to the body shape related information; based on the body shape related information, the second The seat adjustment conversion relationship and the first seat desired state determine the second seat desired state; the second seat desired state is used as the driver's seat state information.
  • the state information of the seat includes at least one of the following information: the target value of the seat adjustment parameter, the up and down position information of the seat, the front and rear position information of the seat, the left and right position information of the seat, the position of the reclining angle of the backrest chair Information, position information of the seat cushion tilt angle.
  • a vehicle including: the driving environment intelligent adjustment device provided by any one of the foregoing embodiments or the driver registration device provided by any one of the foregoing embodiments.
  • an electronic device including a processor, the processor including the driving environment intelligent adjustment device provided by any one of the above embodiments or the driver registration provided by any of the above embodiments Device.
  • an electronic device includes: a memory for storing executable instructions;
  • a processor for communicating with the memory to execute the executable instruction to complete the operation of the driving environment intelligent adjustment method provided by any one of the foregoing embodiments or the driver registration method provided by any one of the foregoing embodiments.
  • a computer storage medium for storing computer readable instructions, which, when executed, execute the intelligent driving environment adjustment method provided by any of the foregoing embodiments or any of the foregoing An operation of the driver registration method provided by an embodiment.
  • the neural network in each embodiment of the present application may be a multi-layer neural network (ie, deep neural network), for example, a multi-layer convolutional neural network, for example, any neural network such as LeNet, AlexNet, GoogLeNet, VGG, ResNet, etc. Network model.
  • Each neural network can use neural networks of the same type and structure, or neural networks of different types and structures. The embodiments of the present application do not limit this.
  • An embodiment of the present application also provides an electronic device, which may be, for example, a mobile terminal, a personal computer (PC), a tablet computer, or a server. 14, which shows a schematic structural diagram of an electronic device 1400 suitable for implementing the terminal device or server of the embodiment of the present application:
  • the electronic device 1400 includes one or more processors and a communication part Etc.
  • the one or more processors are, for example, one or more central processing units (CPUs) 1401, and / or one or more special-purpose processors.
  • the special-purpose processors may serve as the acceleration unit 1413, which may include but not limited to images
  • the processor can be loaded into the random access memory according to the executable instructions stored in the read only memory (ROM) 1402 or from the storage section 1408 (RAM) 1403 executable instructions to perform various appropriate actions and processes.
  • the communication part 1412 may include but is not limited to a network card, and the network card may include but not limited to an IB (Infiniband) network card.
  • the processor may communicate with the read-only memory 1402 and / or the random access memory 1403 to execute executable instructions, connect to the communication unit 1412 through the bus 1404, and communicate with other target devices via the communication unit 1412, thereby completing the embodiment of the present application.
  • the operation corresponding to any of the methods for example, extracting the face features of the driver's image collected by the on-board camera; authenticating the extracted face features based on at least one registered face feature stored in advance; responding to face feature authentication Through the pre-stored correspondence between the registered facial features and the driving environment personalized setting information, determine the driving environment personalized setting information corresponding to the registered facial features corresponding to the facial features; The vehicle sends personalized setting information of the driving environment, or, according to the personalized setting information of the driving environment, controls the vehicle to adjust the driving environment accordingly.
  • RAM 1403 various programs and data necessary for device operation can also be stored.
  • the CPU 1401, ROM 1402, and RAM 1403 are connected to each other through a bus 1404.
  • ROM1402 is an optional module.
  • the RAM 1403 stores executable instructions, or writes executable instructions into the ROM 1402 at runtime, and the executable instructions cause the central processing unit 1401 to perform operations corresponding to the above-mentioned communication method.
  • An input / output (I / O) interface 1405 is also connected to the bus 1404.
  • the communication unit 1412 may be integrated, or may be configured to have multiple sub-modules (for example, multiple IB network cards), and be on the bus link.
  • the following components are connected to the I / O interface 1405: an input section 1406 including a keyboard, a mouse, etc .; an output section 1407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 1408 including a hard disk, etc. ; And a communication section 1409 including a network interface card such as a LAN card, a modem, etc. The communication section 1409 performs communication processing via a network such as the Internet.
  • the driver 1410 is also connected to the I / O interface 1405 as needed.
  • Removable media 1411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like, are installed on the drive 1410 as necessary so that the computer program read out therefrom is installed into the storage portion 1408 as needed.
  • FIG. 14 is only an optional implementation method.
  • the number and types of the components in FIG. 14 can be selected, deleted, added, or replaced according to actual needs; Separate settings or integrated settings can also be used for the setting of different functional components.
  • the acceleration unit 1413 and the CPU 1401 can be separated or the acceleration unit 1413 can be integrated on the CPU 1401. Or on the acceleration unit 1413, etc.
  • embodiments of the present application include a computer program product including a computer program tangibly contained on a machine-readable medium, the computer program containing program code for performing the method shown in the flowchart, the program code may include a corresponding Execute the instructions corresponding to the method steps provided in the embodiments of the present application, for example, extract the face features of the driver image collected by the on-board camera; authenticate the extracted face features based on at least one registered face feature stored in advance; respond to Facial feature authentication is passed, according to the pre-stored correspondence between registered facial features and personalized driving environment setting information, determine the personalized driving environment setting information corresponding to the registered facial features corresponding to the facial features; Vehicles with on-board cameras send personalized setting information for the driving environment, or, based on the personalized setting information for the driving environment, control the vehicle to adjust the driving environment accordingly.
  • the computer program may be downloaded and installed from the network through the communication section 1409, and / or installed from the removable medium 1411.
  • the computer program is executed by the central processing unit (CPU) 1401, the operation of the above-mentioned functions defined in the method of the present application is performed.
  • the method and apparatus of the present application may be implemented in many ways.
  • the method and apparatus of the present application may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware.
  • the above sequence of steps for the method is for illustration only, and the steps of the method of the present application are not limited to the sequence specifically described above unless specifically stated otherwise.
  • the present application may also be implemented as programs recorded in a recording medium, and these programs include machine-readable instructions for implementing the method according to the present application.
  • the present application also covers a recording medium storing a program for executing the method according to the present application.

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Abstract

一种驾驶环境智能调整及驾驶员注册方法和装置、车辆、设备，其中，方法包括：提取车载摄像头采集的驾驶员的图像的人脸特征；基于预先存储的至少一注册人脸特征对提取的人脸特征进行认证；响应于人脸特征认证通过，确定与人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，或者，根据驾驶环境个性化设置信息控制车辆进行驾驶环境的相应调整。基于人脸特征作为驾驶环境个性化智能配置的注册和/或认证手段，提高了认证的准确性和车辆的安全性，并且基于人脸特征比对实现智能化的个性化配置，也有利于保护驾驶员隐私，提高了驾驶舒适度、智能化和用户体验。

Description

驾驶环境智能调整及驾驶员注册方法和装置、车辆、设备
本申请要求在2018年10月19日提交中国专利局、申请号为CN201811224337.5、发明名称为“驾驶环境智能调整及驾驶员注册方法和装置、车辆、设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及计算机视觉技术，尤其是一种驾驶环境智能调整及驾驶员注册方法和装置、车辆、设备。
背景技术
随着车辆的大面积普及，为了提高驾驶员的舒适程度，现有技术提出了对于驾驶员进行个性化设置，为驾驶员提供更舒适的驾驶环境。
发明内容
本申请实施例提供了一种驾驶环境智能调整及驾驶员注册技术方案。
根据本申请实施例的一个方面，提供的一种驾驶环境智能调整方法，包括：
提取车载摄像头采集的驾驶员的图像的人脸特征；
基于预先存储的至少一注册人脸特征对提取的所述人脸特征进行认证；
响应于所述人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与所述人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；
向设置有所述车载摄像头的车辆发送所述驾驶环境个性化设置信息，或者，根据所述驾驶环境个性化设置信息控制所述车辆进行驾驶环境的相应调整。
根据本申请实施例的另一个方面，提供的一种驾驶员注册方法，包括：
获取驾驶员的图像；
提取所述图像的人脸特征；
获取驾驶环境参数的设置信息；
将提取的人脸特征存储为注册人脸特征，将所述驾驶环境参数的设置信息存储为所述注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系。
根据本申请实施例的另一个方面，提供的一种驾驶环境智能调整装置，包括：
特征提取单元，用于提取车载摄像头采集的驾驶员的图像的人脸特征；
人脸特征认证单元，用于基于预先存储的至少一注册人脸特征对提取的所述人脸特征进行认证；
环境信息获取单元，用于响应于所述人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与所述人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；
信息处理单元，用于向设置有所述车载摄像头的车辆发送所述驾驶环境个性化设置信息，或者，根据所述驾驶环境个性化设置信息控制所述车辆进行驾驶环境的相应调整。
根据本申请实施例的另一方面，提供的一种驾驶员注册装置，包括：
图像获取模块，用于获取驾驶员的图像；
人脸特征提取模块，提取所述图像的人脸特征；
参数信息获取模块，获取驾驶环境参数的设置信息；
注册信息存储模块，将提取的人脸特征存储为注册人脸特征，将所述驾驶环境参数的设置信息存储为所述注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系。
根据本申请实施例的另一方面，提供的一种车辆，包括：如上任意一项所述的驾驶环境智能调整装置或如上任意一项所述的驾驶员注册装置。
根据本申请实施例的另一方面，提供的一种电子设备，包括处理器，所述处理器包括如上任意一项所述的驾驶环境智能调整装置或如上任意一项所述的驾驶员注册装置。
根据本申请实施例的另一方面，提供的一种电子设备，包括：存储器，用于存储可执行指令；
以及处理器，用于与所述存储器通信以执行所述可执行指令从而完成如上任意一项所述驾驶环境智能调整方法或如上任意一项所述的驾驶员注册方法。
根据本申请实施例的另一方面，提供的一种计算机存储介质，用于存储计算机可读取的指令，其特征在于，所述指令被执行时执行如上任意一项所述驾驶环境智能调整方法或如上任意一项所述的驾驶员注册方法的操作。
根据本申请实施例的另一方面，提供的一种计算机程序产品，包括计算机可读代码，其特征在于，当所述计算机可读代码在设备上运行时，所述设备中的处理器执行用于实现如上任意一项所述驾驶环境智能调整方法或如上任意一项所述的驾驶员注册方法的指令。
基于本申请上述实施例提供的一种驾驶环境智能调整及驾驶员注册方法和装置、车辆、设备，提取车载摄像头采集的驾驶员的图像的人脸特征；基于预先存储的至少一注册人脸特征对提取的人脸特征进行认证；响应于人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，或者，根据驾驶环境个性化设置信息控制车辆进行驾驶环境的相应调整，本申请基于人脸特征作为驾驶环境个性化智能配置的注册和/或认证手段，提高了认证的准确性和车辆的安全性，并且基于人脸特征比对实现智能化的个性化配置，也有利于保护驾驶员隐私，提高了驾驶舒适度、智能化和用户体验。
下面通过附图和实施例，对本申请的技术方案做进一步的详细描述。
附图说明
构成说明书的一部分的附图描述了本申请的实施例，并且连同描述一起用于解释本申请的原理。
参照附图，根据下面的详细描述，可以更加清楚地理解本申请，其中：
图1为本申请实施例提供的驾驶环境智能调整方法的一个流程示意图。
图2为本申请实施例提供的驾驶环境智能调整方法的另一流程示意图。
图3为本申请实施例提供的驾驶环境智能调整方法的一个可选示例中驾驶环境个性化设置信息设置示意图。
图4为本申请实施例提供的驾驶环境智能调整方法的又一实施例中驾驶环境参数的设置的流程示意图。
图5为车机坐标系和相机坐标系位置参考图。
图6为相机坐标系空间点平移到车机坐标系的示意结果图。
图7为座椅调节简化相机坐标系和车机坐标系的示意图。
图8为相机坐标系下坐标点(x_1，z_1)旋转到车机坐标系下坐标点(x_0，z_0)示意图。
图9为本申请实施例提供的驾驶环境智能调整的一个可选示例中部分流程示意图。
图10为本申请实施例提供的驾驶环境智能调整方法的另一可选示例的系统示意图。
图11为本申请实施例提供的驾驶环境智能调整装置的一个结构示意图。
图12为本申请实施例提供的驾驶员注册方法的一个流程示意图。
图13为本申请实施例提供的驾驶员注册装置的一个结构示意图。
图14为适于用来实现本申请实施例的终端设备或服务器的电子设备的结构示意图。
具体实施方式
现在将参照附图来详细描述本申请的各种示例性实施例。应注意到：除非另外具体说明，否则在这些实施例中阐述的部件和步骤的相对布置、数字表达式和数值不限制本申请的范围。
同时，应当明白，为了便于描述，附图中所示出的各个部分的尺寸并不是按照实际的比例关系绘制 的。
以下对至少一个示例性实施例的描述实际上仅仅是说明性的，决不作为对本申请及其应用或使用的任何限制。
对于相关领域普通技术人员已知的技术、方法和设备可能不作详细讨论，但在适当情况下，所述技术、方法和设备应当被视为说明书的一部分。
应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦某一项在一个附图中被定义，则在随后的附图中不需要对其进行进一步讨论。
本申请实施例可以应用于计算机系统/服务器，其可与众多其它通用或专用计算系统环境或配置一起操作。适于与计算机系统/服务器一起使用的众所周知的计算系统、环境和/或配置的例子包括但不限于：车载设备、个人计算机系统、服务器计算机系统、瘦客户机、厚客户机、手持或膝上设备、基于微处理器的系统、机顶盒、可编程消费电子产品、网络个人电脑、小型计算机系统﹑大型计算机系统和包括上述任何系统的分布式云计算技术环境，等等。
计算机系统/服务器可以在由计算机系统执行的计算机系统可执行指令(诸如程序模块)的一般语境下描述。通常，程序模块可以包括例程、程序、目标程序、组件、逻辑、数据结构等等，它们执行特定的任务或者实现特定的抽象数据类型。计算机系统/服务器可以在分布式云计算环境中实施，分布式云计算环境中，任务是由通过通信网络链接的远程处理设备执行的。在分布式云计算环境中，程序模块可以位于包括存储设备的本地或远程计算系统存储介质上。
图1为本申请实施例提供的驾驶环境智能调整方法的一个流程示意图。该方法可以由任意电子设备执行，例如终端设备、服务器、移动设备、车载设备等等，如图1所示，该实施例方法包括：
步骤110，提取车载摄像头采集的驾驶员的图像的人脸特征。
可选地，驾驶员的图像可以通过车载摄像头获得，车载摄像头可以为设置在车辆室内(如设置在驾驶区、后视镜或中控台上等)或车辆室外(如车柱)的摄像设备采集获得，而特征提取可以基于神经网络实现，经过神经网络对驾驶员的图像进行特征提取，获得驾驶员的人脸特征，也可以通过其他手段提取驾驶员的图像的人脸特征，本申请实施例不限制采集驾驶员的图像及获取人脸特征的具体手段。可选地，本申请各实施例中的神经网络，分别可以是一个多层神经网络(即：深度神经网络)，其中的神经网络可以是多层的卷积神经网络，例如可以是LeNet、AlexNet、GoogLeNet、VGG、ResNet等任意神经网络模型。各神经网络可以采用相同类型和结构的神经网络，也可以采用不同类型和/或结构的神经网络。本申请实施例不对此进行限制。
在一个可选示例中，该步骤110可以由处理器调用存储器存储的相应指令执行，也可以由被处理器运行的特征提取单元1101执行。
步骤120，基于预先存储的至少一注册人脸特征对提取的人脸特征进行认证。
可选地，可通过识别驾驶员的图像的人脸特征与注册人脸特征进行相似度，判断驾驶员是否可通过认证；当驾驶员的图像的人脸特征与某一注册人脸特征相似度达到预设阈值(人脸特征与该注册人脸特征对应同一人)，可认为该人脸特征通过认证；可选地，注册人脸特征可以通过移动应用端或车机端接收，其注册过程还包括获取对应注册人脸特征的驾驶环境个性化设置信息。
可选地，一个车辆可以包括一个或多个注册人脸特征，注册人脸特征可以存储在移动应用端、车机端本地或存储在云端数据库中，以保证在进行认证时可以获得注册人脸特征，可选地，在存储注册人脸特征的同时还可以存储注册驾驶员的人脸图像，存储注册人脸特征相对存储人脸图像更节省存储空间，提取的人脸特征是计算机可以识别的用于表示人脸特征的计算机表达，相对于人脸图像而言已经进行了脱敏处理，基于人脸特征进行处理，便于保护驾驶员的生理隐私信息不会泄露。
在一个可选示例中，该步骤120可以由处理器调用存储器存储的相应指令执行，也可以由被处理器运行的人脸特征认证单元1102执行。
步骤130，响应于人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息。
可选地，经过注册的注册人脸特征不仅保存注册人脸特征和驾驶环境个性化设置信息，还保存有注 册人脸特征与驾驶环境个性化设置信息之间的对应关系；因此，人脸特征认证通过后，可通过对应关系获取到注册人脸特征对应的驾驶环境个性化设置信息，例如：车内灯光、车内空调温度、车内音乐风格等。
在一个可选示例中，该步骤130可以由处理器调用存储器存储的相应指令执行，也可以由被处理器运行的环境信息获取单元1103执行。
步骤140，向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，或者，根据驾驶环境个性化设置信息控制车辆进行驾驶环境的相应调整。
可选地，当通过与车机端相通信的服务器或移动应用端获取到驾驶环境个性化设置信息，此时，无法直接对车辆进行设置，可将驾驶环境个性化设置信息发送给车辆，车辆的设置是通过车载设备实现的；当通过车机端设置的车载设备获取到驾驶环境个性化设置信息，会根据这些信息对车辆进行相应的调控；驾驶员在使用的过程中如果想改变这些设置的内容，可以通过注册端(如移动应用端或车机端)进行重新的设置驾驶环境个性化设置信息，车机端直接接受或通过接收云端服务器接收注册端发送的驾驶环境个性化设置信息，能够实现实时的驾驶环境个性化设置信息调整。
在一个可选示例中，该步骤140可以由处理器调用存储器存储的相应指令执行，也可以由被处理器运行的信息处理单元1104执行。
基于本申请上述实施例提供的一种驾驶环境智能调整方法，提取车载摄像头采集的驾驶员的图像的人脸特征；基于预先存储的至少一注册人脸特征对提取的人脸特征进行认证；响应于人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，或者，根据驾驶环境个性化设置信息控制车辆进行驾驶环境的相应调整，本申请基于人脸特征作为驾驶环境个性化智能配置的注册和/或认证手段，提高了认证的准确性和车辆的安全性，并且基于人脸特征比对实现智能化的个性化配置，也有利于保护驾驶员隐私，提高了驾驶舒适度、智能化和用户体验。
可选地，驾驶环境个性化设置信息可以包括但不限于以下至少之一：温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息等。可选地，可对车辆内温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息等一项或多项进行设置，除了上述列举的信息，本领域技术人员应当理解，对于驾驶环境有影响的其他信息也同样属于本申请可设置的驾驶环境个性化设置信息。
在一个或多个可选的实施例中，还包括：
响应于人脸特征认证不通过，发出注册申请提示信息或者认证不通过提示信息。
可选地，当注册人脸特征中不存在与人脸特征匹配的注册人脸特征时，被请求设备(移动应用端或车机端等)可发出认证不通过提示信息，说明该驾驶员未对该车辆进行注册，无法获取到驾驶环境个性化设置信息；或者，被请求设备可发出注册申请提示信息，提示该驾驶员进行注册，完成注册后该驾驶员即可获得驾驶环境个性化设置信息。
图2为本申请实施例提供的驾驶环境智能调整方法的另一流程示意图。如图2所示，本申请实施例方法包括：
步骤210，提取车载摄像头采集的驾驶员的图像的人脸特征。
本申请实施例中步骤210与上述实施例的步骤110类似，可参照上述实施例对该步骤进行理解，在此不再赘述。
步骤220，通过驾驶员注册流程获取驾驶员的注册人脸特征、驾驶环境个性化设置信息以及二者之间的对应关系。
以上步骤210和步骤220之间的顺序可调整，即可先执行步骤210再执行220，或先执行步骤220再执行步骤210。
可选地，通过获取驾驶员的注册人脸特征、驾驶环境个性化设置信息以及二者之间的对应关系实现驾驶员注册，本申请实施例的驾驶员注册基于注册人脸特征作为唯一的识别信息，提高了注册驾驶员识别的准确性，减少了由于基于性别等其他信息作为识别信息产生的可伪造的问题。
步骤230，基于预先存储的至少一注册人脸特征对提取的人脸特征进行认证。
本申请实施例中步骤230与上述实施例的步骤120类似，可参照上述实施例对该步骤进行理解，在此不再赘述。
步骤240，响应于人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息。
本申请实施例中步骤240与上述实施例的步骤130类似，可参照上述实施例对该步骤进行理解，在此不再赘述。
步骤250，向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，或者，根据驾驶环境个性化设置信息控制车辆进行驾驶环境的相应调整。
本申请实施例中步骤250与上述实施例的步骤140类似，可参照上述实施例对该步骤进行理解，在此不再赘述。
本申请实施例在进行人脸特征认证之前，需要进行驾驶员注册，使车辆获取至少一个注册人脸特征，以保证在获取驾驶员的人脸特征之后可以对该人脸特征进行认证，可选地，驾驶员注册流程包括：
获取驾驶员的图像；
提取图像的人脸特征；
获取驾驶环境参数的设置信息；
将提取的人脸特征存储为注册人脸特征，将驾驶环境参数的设置信息存储为注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和驾驶环境个性化设置信息之间的对应关系。
可选地，获取请求注册的驾驶员的图像可通过移动应用端或车机端实现，移动应用端和车机端都设置有摄像头等摄像装置，通过摄像头采集驾驶员的图像，对图像进行人脸特征提取获得人脸特征，通过设备接收驾驶员的输入的驾驶环境参数的设置信息，或从车机端提取车辆中设置的驾驶参数的设置信息；为保证注册人脸特征与驾驶环境个性化设置信息一一对应，在存储时，还保存注册人脸特征和驾驶环境个性化设置信息之间的对应关系；在后续需要获取驾驶环境个性化设置信息时，只需进行人脸特征匹配即可通过对应关系获得对应的驾驶环境个性化设置信息，无需复杂的过程，基于人脸特征实现智能化的个性化配置，在保护驾驶员隐私的前提下实现了快速的驾驶环境个性化设置信息获取。
图3为本申请实施例提供的驾驶环境智能调整方法的一个可选示例中驾驶环境个性化设置信息设置示意图。如图3所示，在移动应用端(如：手机、平板电脑等)设置完成的驾驶环境个性化设置信息，通过将注册人脸特征作为唯一识别方式；其中驾驶环境个性化设置信息包括温度(AC Temperature)、环境光色(Ambient Light Color)和音乐风格(Music Style)，该移动应用端中还可以显示注册驾驶员的人脸图像，还可以为注册驾驶员设置名称(Name)，这些驾驶环境个性化设置信息所在的注册存储单位可以保存在移动应用端的寄存器中；其中Name是可以修改的，在完成注册之后，也可以对Name进行修改，例如：注册的时候是A，注册后修改为B；以上驾驶环境个性化设置信息都可以进行设置、更改和保存，但是，在执行操作之前，需要对人脸特征进行认证，只有认证通过之后，才可以进行操作。
可选地，获取驾驶员的图像，包括：
通过移动应用端和/或车载摄像头获取驾驶员的图像。
本实施例中，可通过移动应用端和/或车载摄像头获取驾驶员的图像，即，驾驶员请求注册时，可以自行选择方便的端口进行，可通过移动应用端(如：手机、平板电脑等)进行注册；也可以通过车机端注册，通过车机端注册时，通过车载摄像头来采集驾驶员的图像，此时车载摄像头可以设置在驾驶座前方，对应车机端的驾驶环境个性化设置信息的采集可以通过驾驶员通过车机端的交互设备输入或通过车载设备读取车辆设置数据获得。
可选地，通过移动应用端获取驾驶员的图像，包括：
通过从移动应用端存储的至少一个图像中获取驾驶员的图像，或
通过移动应用端设置的摄像装置采集获得驾驶员的图像。
本实施例通过移动应用端获取驾驶员的图像，本申请实施例所指移动应用端包括但不限：手机、平板电脑等具有摄像和存储功能的设备；由于移动应用端具有摄像和存储功能，获取驾驶员图像的方式，可通过在移动应用端中存储的图像中选择获取驾驶员的图像，或者通过移动应用端的摄像头采集获取驾 驶员的图像。
可选地，获取驾驶环境参数的设置信息，包括：
通过移动应用端和/或车载设备接收驾驶环境参数的设置信息。
本申请实施例中，在获取了注册人脸特征之后，还需要获得对应的驾驶环境参数的设置信息，驾驶环境参数包括但不限于：车内温度、灯光、音乐风格、座椅状态、音响设置等与驾驶环境相关的参数，这些环境参数可根据驾驶员通过设备进行输入设置，例如：通过移动应用端将车内温度调整到22度、灯光颜色设置为暖黄等。
可选地，获取驾驶环境参数的设置信息的方式，除了上述通过移动应用端和/或车载设备接收，还可以通过车载设备采集车辆中的驾驶环境参数的设置信息。
两种方式可以结合使用或单独使用，可以在移动应用端设置部分驾驶环境参数，再通过车载设备采集车辆中的部分驾驶环境参数，例如：通过移动应用端设置灯光和温度，通过车载设备采集车辆中的座椅状态；或全部通过车载设备采集，由于通过设备设置时，驾驶员可能不在车内，对车内外环境不是很了解，因此，设置的信息可能存在不准确的可能，通过车载设备采集的是通过驾驶员手动调节或车辆自动配置的符合驾驶员个性的设置信息，在驾驶员使用时，更舒适。
可选地，获取驾驶环境参数的设置信息，包括：
通过车载设备采集车辆中的驾驶环境参数的设置信息；
基于采集的驾驶环境参数的设置信息对注册人脸特征对应的驾驶环境个性化设置信息进行更新操作。
如上述实施例所指出的，通过设备(移动应用端等)设置时，驾驶员可能不在车内，对车内外环境不是很了解，因此，设置的信息可能存在不准确的可能，还存在一种情况时，在车辆行驶过程中车内外环境发生了变化，之前设置的信息已经不适合当前环境，例如：开车过程中由于时间变化，外部环境变暗，为了方便驾驶，此时需要改变灯光信息；出现在驾驶过程中需要对驾驶环境参数进行调整的情况，驾驶员可直接通过人脸特征认证后对车内驾驶环境参数进行设置，设置后，通过车载设备对驾驶环境参数的设置信息进行采集，并基于该驾驶环境参数的设置信息对注册人脸特征对应的驾驶环境个性化设置信息进行更新操作，以使设置的驾驶环境个性化设置信息更符合驾驶员的需求。
可选地，本申请实施例方法还包括：根据接收的管理指令对存储的驾驶环境个性化设置信息进行以下至少一个操作：删除、编辑、权限设置等。
本申请实施例中，可实现具有权限的管理人员通过管理指令对驾驶环境个性化设置信息进行操作，例如：车主将车辆中某一个驾驶员的注册人脸特征和驾驶环境个性化设置信息删除，或车主将某一个驾驶员的权限限制在仅能调节座椅状态等；通过对驾驶环境个性化设置信息的操作，实现了个性化权限管理。
在一个或多个可选的实施例中，注册人脸特征和驾驶环境个性化设置信息之间的对应关系存储在以下至少一个位置：移动应用端、服务器、车载设备等。
本实施例中，注册人脸特征的信息和关系可以存储在移动应用端、服务器或车载设备等位置，当存储在移动应用端时，车机端与移动应用端相互通信，车机端获取驾驶员图像之后可以从移动应用端下载相应信息进行认证，或将人脸特征传输到移动应用端中进行认证，完成认证后移动应用端将驾驶环境个性化设置信息发送给车机端；当存储在车载设备中时，车机端无需与外界通信，直接将车载摄像头获得的驾驶员的人脸特征与车载设备存储的注册人脸特征进行认证即可；当存储在服务器时，需要服务器与车载设备相互通信，车机端获取驾驶员图像之后可以从服务器下载相应信息进行认证，或将人脸特征上传到服务器中进行认证，完成认证后服务器将驾驶环境个性化设置信息发送给车机端。
可选地，上述实施例中步骤140中向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，包括：
通过与车辆相通信的服务器或移动应用端向设置有车载摄像头的车辆发送驾驶环境个性化设置信息。
本申请实施例中以服务器或移动应用端作为认证主体，在服务器或移动应用端中实现人脸特征认证，完成认证之后将存储在服务器或移动应用端中的驾驶环境个性化设置信息发送给车机端，至于如何根据 驾驶环境个性化设置信息进行设置在车机端完成，不受服务器或移动应用端的管理控制，服务器或移动应用端只完成驾驶环境个性化设置信息发送给车机端。
可选地，上述实施例中步骤140中根据驾驶环境个性化设置信息对设置有车载摄像头的车辆进行驾驶环境的相应调整，包括：
通过车载设备根据驾驶环境个性化设置信息对设置有车载摄像头的车辆进行驾驶环境的相应调整。
本申请实施例实现的是以车机端作为认证主体，在车载设备中完成人脸特征认证，此时存在两种可能：注册人脸特征和驾驶环境个性化设置信息存储在车机端，或注册人脸特征和驾驶环境个性化设置信息存储在移动应用端或服务器；驾驶环境个性化设置信息存储在车机端时，车载设备直接调用驾驶环境个性化设置信息对车辆进行相应设置，而驾驶环境个性化设置信息存储在移动应用端或服务器时，需要从移动应用端或服务器下载注册人脸特征对应的驾驶环境个性化设置信息，并基于该驾驶环境个性化设置信息对车辆进行相应的设置。
图4为本申请实施例提供的驾驶环境智能调整方法的又一实施例中驾驶环境参数的设置的流程示意图。该实施例中驾驶环境参数的设置信息包括座椅状态信息；获取驾驶环境参数的设置信息，如图4所示，包括：
步骤410，对驾驶员的图像进行检测，获得检测结果。
对于进入车辆中的驾驶员进行采集图像，以采集的驾驶员的图像实现检测，检测可以基于神经网络或其他方式实现，本申请实施例不限制对驾驶员的图像进行检测的具体方式。
步骤420，根据检测结果确定驾驶员的体型相关信息和/或人脸高度信息。
可选地，对于确定驾驶员的体型相关信息和确定驾驶员的人脸高度信息通常对应不同的检测结果，即，对于驾驶员的检测可以分别基于一个或两个神经网络进行检测，以获得对应体型相关信息和/或人脸高度信息的检测结果，体型相关信息可以包括但不限于：人种、性别等与驾驶员乘车相关的信息(如：胖瘦程度、腿长信息、骨架大小信息、手长信息等)有影响的信息。例如：基于关键点检测网络对人脸参考点进行检测，以获得的人脸参考点确定人脸高度信息；基于属性检测的神经网络对驾驶员的图像进行属性检测，以确定体型相关信息，或者通过人体或人脸检测的结果可确定驾驶员的体型相关信息，或通过分类神经网络直接检测获得体型相关信息，例如：通过人脸识别到的性别，可以获得该驾驶员的骨架大小信息，女性的骨架偏小，而男性的骨架偏大。
以检测结果确定体型相关信息和/或人脸高度信息可以直接将检测结果作为体型相关信息和/或人脸高度信息，还可以对检测结果进行处理后获得体型相关信息和/或人脸高度信息。
步骤430，基于体型相关信息和/或人脸高度信息，确定驾驶员的座椅状态信息。
可选地，人体舒适的坐姿不仅与坐姿高度有关，还与体型相关，为了提供更舒适的座椅调节位置，本申请实施例通过获得驾驶员的体型相关信息和/或人脸高度信息，来确定座椅的调节信息，本申请实施例根据座椅的调节信息调整的座椅为驾驶员提供了更适合的坐姿，提高了驾驶员的使用舒适度。
可选地，检测结果包括人脸参考点坐标；
步骤410包括：对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的人脸参考点坐标。
可选地，人脸参考点可以是人脸上的任意一点，可以是人脸关键点，也可以是人脸上的其他位置点，由于车辆行驶过程中，驾驶员的视野具有重要作用；对于驾驶员来说，保证驾驶员在驾驶过程中的双目高度，可以提高驾驶安全性，因此，人脸参考点可以设置为与眼睛相关的点，例如：确定双眼位置的至少一个关键点，或眉心位置点等；本申请实施例不限制具体人脸参考点的数量和位置，以可确定人脸高度为准。
在一些可选示例中，人脸参考点包括至少一个人脸关键点和/或至少一个人脸其他位置点；步骤410包括：对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的至少一个人脸关键点坐标；
和/或，基于至少一个人脸关键点坐标确定至少一个人脸其他位置点。
可选地，通过神经网络可以对人脸关键点的位置进行确定，例如：人脸21个关键点、人脸106个关键点、人脸240个关键点中的一个或多个，通过不同网络获得的关键点个数不同，可以包括五官的关 键点、或者还可以包括脸部轮廓的关键点，关键点疏密不同，导致获得的关键点个数也不同；通过获得的关键点中的一个或多个作为人脸参考点只需根据具体情况进行选择不同部位即可，本申请实施例不限制人脸关键点的位置和个数。
可选地，参考点还可以是基于人脸关键点的检测结果确定的人脸图像上的人脸其他位置点，这些人脸其他位置点可以不是关键点，即为人脸上的任意位置点，但其位置可根据人脸关键点进行确定，例如：眉心位置，可基于双眼的关键点和眉毛的关键点确定。
步骤420包括：将人脸参考点坐标从相机坐标系转换到车机坐标系；
基于在车机坐标系下的人脸参考点坐标确定驾驶员的人脸高度信息。
可选地，由于人脸参考点是通过相机采集的图像获得的，该人脸参考点对应的是相机坐标系，而在确定座椅信息时，需要在车机坐标系下进行确定，因此，需要通过将人脸参考点从相机坐标系转换到车机坐标系。
一个可选示例中，可采用现有技术中常用的坐标系转换方式将眉心位置坐标从相机坐标系转换到车机坐标系，例如：图5为车机坐标系和相机坐标系位置参考图，其中车机坐标系中：y轴为车前轮车轴，x轴与左边上边缘平行，z轴垂直地面向下。图6为相机坐标系空间点平移到车机坐标系的示意结果图。如图6所示：将相机坐标系原点Oc平移到车机坐标系原点O。已知Oc在车机坐标系下为(Xwc,Ywc,Zwc)，在相机坐标系下Oc为(0,0,0)，平移到车机坐标系原点O(0,0,0)点有：
0＝0–Xwc      公式(1)
0＝0–Ywc     公式(2)
0＝0–Zwc     公式(3)
由公式(1)，(2)，(3)得到平移向量T为
[Xwc Ywc Zwc]      公式(4)
完成坐标系平移转换。
图7为座椅调节简化相机坐标系和车机坐标系的示意图。如图7所示，在实际座椅调节过程中，车机坐标系下的X轴是不做调整的，则相机坐标系下坐标点转换到车机坐标系下简化为二维坐标系下的旋转操作。图8为相机坐标系下坐标点(x 1，z 1)旋转到车机坐标系下坐标点(x 0，z 0)示意图。如图8所示，假设在相机坐标系下检测到驾驶员头部坐标点为(y 1，z 1),经过旋转角度α，即摄像头的安装角度，得到车机坐标系下坐标点(x 0，z 0)。
根据图7两坐标系下坐标点的转换示意图提供的转换过程如下：
x 0＝-y 1sinα+z 1cosα    公式(5)
z 0＝y 1cosα+z 1sinα   公式(6)
y 0＝-x 1    公式(7)
由公式(5)、(6)、(7)可得：
Figure PCTCN2019111930-appb-000001
由公式(4)，(8)可得最后相机坐标系下坐标点旋转平移到车机坐标系下坐标为：
Figure PCTCN2019111930-appb-000002
通过坐标系转换，可确定驾驶员在车辆中的人脸高度信息，即可确定人脸高度与座椅之间的相对位置关系，可获得该人脸高度信息对应的期望的座椅状态信息。
可选地，体型相关信息包括人种信息和/或性别信息；
步骤410包括：将驾驶员的图像输入用于属性检测的神经网络进行属性检测，得到神经网络输出的属性检测结果。
可选地，本申请实施例中通过神经网络实现属性检测，该属性检测结果包括驾驶员的人种信息和/或性别信息；可选地，该神经网络可以是包括至少一个分支的分类网络，包括一个分支的情况下，对人 种信息或性别信息进行分类，包括两个分支的情况下，实现对人种信息和性别信息进行分类；以确定驾驶员的人种分类和性别分类。
步骤420包括：基于属性检测结果获得图像对应的驾驶员的人种信息和/或性别信息。
可选地，不同性别的体型差距较大，同样上身高度的男性和女性由于体型差距巨大，对应的舒适的座椅位置也存在较大差异，因此，为了提供更舒适的座椅位置，需要获得驾驶员的性别信息；除了性别，不同人种(如：黄种人、白种人、黑种人等)的体型之间也存在较大差异，例如：黑种人通常体型较为壮硕，在座椅前后位置上需要更大空间，对于不同人种，可通过大数据计算获得适合每种人种的体型的座椅位置参照数据。
可选地，步骤430包括：
获得预设的与体型和/或人脸高度相关的座椅调节转换关系；
基于体型相关信息和/或人脸高度信息、及座椅调节转换关系，确定驾驶员对应的座椅期望状态，将座椅期望状态作为驾驶员的座椅状态信息。
可选地，座椅调节转换关系可以包括但不限于转换公式或对应关系表等，转换公式可将体型和/或人脸高度输入公式，获得座椅期望状态对应的数据，对应关系表可直接基于体型和/或人脸高度查表获得座椅期望状态对应的数据，该对应关系表可以通过大数据统计获得，或其他方式获得，本申请实施例不限制获得对应关系表的具体方式。
在一个可选示例中，对于座椅状态的确定，人种的不同和/或性别的不同，座椅期望状态也不同，针对不同的性别和人种可以组合得到多组对应的公式，如：黄种人+男性对于一个座椅调节公式，具体到每个公式输入的眉心坐标(x，y，z)和靠背调整角度每一维度都对应一个三次一元函数，例如：
x out＝a 1x 3+b 1x 2+c 1x+d 1      公式(10)
y out＝a 2y 3+b 2y 2+c 2y+d 2      公式(11)
z out＝a 3z 3+b 3z 2+c 3z+d 3     公式(12)
angle out＝a 4x 3+b 4x 2+c 4x+d 4     公式(13)
通过上述公式(10)、(11)、(12)和(13)可基于眉心坐标在x轴，y轴，z轴方向上的坐标确定最终计算得到的座椅期望状态(x out，y out，z out，angle out)经过最终的电机调整分配公式得到4个电机的调整量；其中，x out表示座椅的前后位置信息，y out表示坐垫倾斜角度的信息，z out表示座椅的上下位置信息，angle out表示靠背椅倾斜角度的信息；其中，a 1，b 1，c 1，d 1，a 2，b 2，c 2，d 2，a 3，b 3，c 3，d 3，a 4，b 4，c 4，d 4为经过多次实验获得的常量。
在另一个可选示例中，还可以仅基于眉心坐标在z轴方向上的坐标(即眉心高度)确定最终计算得到的座椅期望状态(x out，y out，z out，angle out)，可基于以下公式实现：
x out＝a 5z+d 5    公式(14)
y out＝a 6z+d 6     公式(15)
z out＝a 7z+d 7       公式(16)
angle out＝a 8z+d 8      公式(17)
其中，x out表示座椅的前后位置信息，y out表示坐垫倾斜角度的信息，z out表示座椅的上下位置信息，angle out表示靠背椅倾斜角度的信息；其中，a 5，d 5，a 6，d 6，a 7，d 7，a 8，d 8为经过多次实验获得的常量。
图9为本申请实施例提供的驾驶环境智能调整的一个可选示例中部分流程示意图。如图9所示，上述实施例中，步骤430包括：
步骤901，获得预设的与人脸高度相关的第一座椅调节转换关系。
可选地，座椅调节转换关系可以包括但不限于转换公式或对应关系表等，转换公式可将人脸高度输入公式，获得座椅期望状态对应的数据，对应关系表可直接基于人脸高度查表获得座椅期望状态对应的数据，该对应关系表可以通过大数据统计获得，或其他方式获得，本身实施例不限制获得对应关系表的具体方式。
步骤902，基于人脸高度信息和第一座椅调节转换关系，确定驾驶员对应的第一座椅期望状态。
步骤903，获得预设的与体型相关信息相关的第二座椅调节转换关系。
可选地，本实施例中，体现相关信息对应第二座椅调节转换关系，该第二座椅调节转换关系与第一座椅调节转换关系不同，其形式可以包括但不限于转换公式或对应关系表等，通过第二座椅调节转换关系结合体型相关信息和第一座椅期望状态可确定第二座椅期望状态。
步骤904，基于体型相关信息、第二座椅调节转换关系和第一座椅期望状态，确定第二座椅期望状态。
步骤905，将第二座椅期望状态作为驾驶员的座椅状态信息。
本实施例通过体型相关信息和人脸高度信息结合确定座椅状态信息，其中，体型相关信息中人种和性别结合获得的分类数量有限，并且只要确定为一个组合，例如：男性+黄种人，就适用于这个分类下的所有驾驶员，个性化不足，但信息易于获得；而人脸高度信息更加个性化，不同驾驶员对应的调节信息都有可能不同，因此，本实施例实现了通过通用信息结合个性化信息提高座椅状态信息的准确性。
可选地，座椅的状态信息包括但不限于以下至少一个信息：座椅调节参数的目标值、座椅的上下位置信息、座椅的前后位置信息、座椅的左右位置信息、靠背椅倾斜角度的位置信息、坐垫倾斜角度的位置信息。
可选地，为了实现多方位调节座椅，需要在多方向上对座椅进行调节，除了通常包括的上下、前后、左右调节量，还包括靠背椅倾斜角度的信息、坐垫倾斜角度的信息。比如：直接输出座椅最终要调节到的上下左右前后等等各个调节参数的目标值，而具体如何调整达到目标值，可通过电机或者其他设备来进行处理实现。
图10为本申请实施例提供的驾驶环境智能调整方法的另一可选示例的系统示意图。如图10所示为该软件系统的示意图，系统分为三大部分，移动端应用、云端服务器以及车机端控制器，三个部分之间的数据都是通过网络进行传输；移动端应用安装在手机或者平板等移动设备上，能够进行人脸注册以及驾驶员驾驶环境个性化设置信息的设置，并将数据传给云端服务器；车机端控制器安装在车上，能够进行车内的灯光颜色、温度、音乐播放以及座椅的调控，并使用摄像头将驾驶员登陆需要的人脸信息上传至云服务器端；云端服务器使用数据库对该系统中的数据进行存取；具体的实现方案可以根据实际应用场景进行调整。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
图11为本申请实施例提供的驾驶环境智能调整装置的一个结构示意图。该实施例的装置可用于实现本申请上述各驾驶环境智能调整方法实施例。如图11所示，该实施例的装置包括：
特征提取单元1101，用于提取车载摄像头采集的驾驶员的图像的人脸特征。
人脸特征认证单元1102，用于基于预先存储的至少一注册人脸特征对提取的人脸特征进行认证。
环境信息获取单元1103，用于响应于人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息。
信息处理单元1104，用于向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，或者，根据驾驶环境个性化设置信息控制车辆进行驾驶环境的相应调整。
基于本申请上述实施例提供的一种驾驶环境智能调整装置，本申请基于人脸特征作为驾驶环境个性化智能配置的注册和/或认证手段，提高了认证的准确性和车辆的安全性，并且基于人脸特征比对实现智能化的个性化配置，也有利于保护驾驶员隐私，提高了驾驶舒适度、智能化和用户体验。
可选地，驾驶环境个性化设置信息包括以下至少之一：温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息。
在一个或多个可选的实施例中，本申请实施例装置还包括：
提示信息单元，用于响应于人脸特征认证不通过，发出注册申请提示信息或者认证不通过提示信息。
在一个或多个可选的实施例中，本申请实施例装置还包括：驾驶员注册单元，用于通过驾驶员注册流程获取驾驶员的注册人脸特征、驾驶环境个性化设置信息以及二者之间的对应关系。
可选地，驾驶员注册单元，包括：
图像获取模块，用于获取驾驶员的图像；
人脸特征提取模块，用于提取图像的人脸特征；
参数信息获取模块，用于获取驾驶环境参数的设置信息；
注册信息存储模块，用于将提取的人脸特征存储为注册人脸特征，将驾驶环境参数的设置信息存储为注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和驾驶环境个性化设置信息之间的对应关系。
可选地，图像获取模块，用于通过移动应用端和/或车载摄像头获取驾驶员的图像。
可选地，图像获取模块，用于通过从移动应用端存储的至少一个图像中获取驾驶员的图像，或通过移动应用端设置的摄像装置采集获得驾驶员的图像。
可选地，参数信息获取模块，用于通过移动应用端和/或车载设备接收驾驶环境参数的设置信息。
可选地，参数信息获取模块，用于通过车载设备采集车辆中的驾驶环境参数的设置信息。
可选地，参数信息获取模块，用于通过车载设备采集车辆中的所述驾驶环境参数的设置信息；基于所述采集的驾驶环境参数的设置信息对所述注册人脸特征对应的所述驾驶环境个性化设置信息进行更新操作。
可选地，驾驶员注册单元，还包括：
信息管理模块，用于根据接收的管理指令对存储的驾驶环境个性化设置信息进行以下至少一个操作：删除、编辑、权限设置等。
可选地，注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系存储在以下至少一个位置：移动应用端、服务器、车载设备等。
可选地，信息处理单元在向设置有车载摄像头的车辆发送驾驶环境个性化设置信息时，用于通过与车辆相通信的服务器或移动应用端向设置有车载摄像头的车辆发送驾驶环境个性化设置信息。
可选地，信息处理单元在根据驾驶环境个性化设置信息控制对设置有车载摄像头的车辆进行驾驶环境的相应调整时，用于通过车载设备根据驾驶环境个性化设置信息对设置有车载摄像头的车辆进行驾驶环境的相应调整。
在一个或多个可选的实施例中，驾驶环境参数的设置信息包括：座椅状态信息；
参数信息获取模块，用于对驾驶员的图像进行检测，获得检测结果；根据检测结果确定驾驶员的体型相关信息和/或人脸高度信息；基于体型相关信息和/或人脸高度信息，确定驾驶员的座椅状态信息。
可选地，检测结果包括人脸参考点坐标；
参数信息获取模块在对驾驶员的图像进行检测，获得检测结果时，用于对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的人脸参考点坐标；
参数信息获取模块在检测结果确定驾驶员的人脸高度信息时，用于将人脸参考点坐标从相机坐标系转换到车机坐标系；基于在车机坐标系下的人脸参考点坐标确定驾驶员的人脸高度信息。
可选地，人脸参考点包括至少一个人脸关键点和/或至少一个人脸其他位置点；
参数信息获取模块在对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的人脸参考点坐标时，用于对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的至少一个人脸关键点坐标；和/或，基于至少一个人脸关键点坐标确定至少一个人脸其他位置点。
可选地，体型相关信息包括人种信息和/或性别信息；
参数信息获取模块在对驾驶员的图像进行检测，获得检测结果时，用于将驾驶员的图像输入用于属性检测的神经网络进行属性检测，得到神经网络输出的属性检测结果；
参数信息获取模块在根据检测结果确定驾驶员的体型相关信息时，用于基于属性检测结果获得图像对应的驾驶员的人种信息和/或性别信息。
可选地，参数信息获取模块在基于体型相关信息和/或人脸高度信息，确定驾驶员的座椅状态信息时，用于获得预设的与体型和/或人脸高度相关的座椅调节转换关系；基于体型相关信息和/或人脸高度信息和座椅调节转换关系，确定驾驶员对应的座椅期望状态，将座椅期望状态作为驾驶员的座椅状态信 息。
可选地，参数信息获取模块在基于体型相关信息和/或人脸高度信息，确定驾驶员的座椅状态信息时，用于获得预设的与人脸高度相关的第一座椅调节转换关系；基于人脸高度信息和第一座椅调节转换关系，确定驾驶员对应的第一座椅期望状态；获得预设的与体型相关信息相关的第二座椅调节转换关系；基于体型相关信息、第二座椅调节转换关系和第一座椅期望状态，确定第二座椅期望状态；将第二座椅期望状态作为驾驶员的座椅状态信息。
可选地，座椅的状态信息包括以下至少一个信息：座椅调节参数的目标值、座椅的上下位置信息、座椅的前后位置信息、座椅的左右位置信息、靠背椅倾斜角度的位置信息、坐垫倾斜角度的位置信息。
本公开实施例提供的驾驶环境智能调整装置任一实施例的工作过程、设置方式及相应技术效果，均可以参照本公开上述相应方法实施例的具体描述，限于篇幅，在此不再赘述。
图12为本申请实施例提供的驾驶员注册方法的一个流程示意图。该方法可以由任意电子设备执行，例如终端设备、服务器、移动设备、车载设备等等，如图12所示，该实施例方法包括：
步骤1210，获取驾驶员的图像。
可选地，获取请求注册的驾驶员的图像可通过移动应用端或车机端实现，移动应用端和车机端都设置有摄像头等摄像装置，通过摄像头采集驾驶员的图像。
在一个可选示例中，该步骤1210可以由处理器调用存储器存储的相应指令执行，也可以由被处理器运行的图像获取模块1301执行。
步骤1220，提取图像的人脸特征。
可选地，可通过卷积神经网络对图像进行特征提取，获得人脸特征，还可以基于其他手段获得图像的人脸特征，本申请实施例不限制获得人脸特征的具体手段。
在一个可选示例中，该步骤1220可以由处理器调用存储器存储的相应指令执行，也可以由被处理器运行的人脸特征提取模块1302执行。
步骤1230，获取驾驶环境参数的设置信息。
可选地，获取请求注册的驾驶员的图像可通过移动应用端或车机端实现，移动应用端和车机端都设置有摄像头等摄像装置，通过摄像头采集驾驶员的图像。
在一个可选示例中，该步骤1230可以由处理器调用存储器存储的相应指令执行，也可以由被处理器运行的参数信息获取模块1303执行。
步骤1240，将提取的人脸特征存储为注册人脸特征，将驾驶环境参数的设置信息存储为注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和驾驶环境个性化设置信息之间的对应关系。
在一个可选示例中，该步骤1230可以由处理器调用存储器存储的相应指令执行，也可以由被处理器运行的注册信息存储模块1304执行。
本申请实施例为保证注册人脸特征与驾驶环境个性化设置信息一一对应，在存储时，还保存注册人脸特征和驾驶环境个性化设置信息之间的对应关系；在后续需要获取驾驶环境个性化设置信息时，只需进行人脸特征匹配即可通过对应关系获得对应的驾驶环境个性化设置信息，无需复杂的过程，基于人脸特征实现智能化的个性化配置，在保护驾驶员隐私的前提下实现了快速的驾驶环境个性化设置信息获取。
可选地，驾驶环境个性化设置信息包括以下至少之一：温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息等。
本申请实施例中设置的驾驶环境个性化设置信息，可为驾驶员提供更舒适的驾驶环境，更符合驾驶员的个人习惯，即对于同一车辆的不同驾驶员可设置不同的驾驶环境，更具个性化，提高了驾驶舒适度，可选地，可对车辆内温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息等信息中的一项或多项进行设置，除了上述列举的信息，本领域技术人员应当理解，对于驾驶环境有影响的其他信息也同样属于本申请可设置的驾驶环境个性化设置信息。
在一个或多个可选的实施例中，步骤1210包括：
通过移动应用端和/或车载摄像头获取驾驶员的图像。
本实施例中，可通过移动应用端和/或车载摄像头获取驾驶员的图像，即，驾驶员请求注册时，可 以自行选择方便的端口进行，可通过移动应用端(如：手机、平板电脑等)进行注册；也可以通过车机端注册，通过车机端注册时，通过车载摄像头来采集驾驶员的图像，此时车载摄像头可以设置在驾驶座前方，对应车机端的驾驶环境个性化设置信息的采集可以通过驾驶员通过车机端的交互设备输入或通过车载设备读取车辆设置数据获得。
可选地，通过移动应用端获取驾驶员的图像，包括：
通过从移动应用端存储的至少一个图像中获取驾驶员的图像，或
通过移动应用端设置的摄像装置采集获得驾驶员的图像。
本实施例通过移动应用端获取驾驶员的图像，本申请实施例所指移动应用端包括但不限：手机、平板电脑等具有摄像和存储功能的设备；由于移动应用端具有摄像和存储功能，获取驾驶员图像的方式，可通过在移动应用端中存储的图像中选择获取驾驶员的图像，或者通过移动应用端的摄像头采集获取驾驶员的图像。
在一个或多个可选的实施例中，步骤1230包括：
通过移动应用端和/或车载设备接收驾驶环境参数的设置信息。
本申请实施例中，在获取了注册人脸特征之后，还需要获得对应的驾驶环境参数的设置信息，驾驶环境参数包括但不限于：车内温度、灯光、音乐风格、座椅状态、音响设置等与驾驶环境相关的参数，这些环境参数可根据驾驶员通过设备进行输入设置，例如：通过移动应用端将车内温度调整到22度、灯光颜色设置为暖黄等。
可选地，获取驾驶环境参数的设置信息的方式，除了上述通过移动应用端和/或车载设备接收，还可以通过车载设备采集车辆中的驾驶环境参数的设置信息。
两种方式可以结合使用或单独使用，可以在移动应用端设置部分驾驶环境参数，再通过车载设备采集车辆中的部分驾驶环境参数，例如：通过移动应用端设置灯光和温度，通过车载设备采集车辆中的座椅状态；或全部通过车载设备采集，由于通过设备设置时，驾驶员可能不在车内，对车内外环境不是很了解，因此，设置的信息可能存在不准确的可能，通过车载设备采集的是通过驾驶员手动调节或车辆自动配置的符合驾驶员个性的设置信息，在驾驶员使用时，更舒适。
可选地，步骤1230包括：
通过车载设备采集车辆中的驾驶环境参数的设置信息；
基于采集的驾驶环境参数的设置信息对注册人脸特征对应的驾驶环境个性化设置信息进行更新操作。
如上述实施例所指出的，通过设备(移动应用端等)设置时，驾驶员可能不在车内，对车内外环境不是很了解，因此，设置的信息可能存在不准确的可能，还存在一种情况时，在车辆行驶过程中车内外环境发生了变化，之前设置的信息已经不适合当前环境，例如：开车过程中由于时间变化，外部环境变暗，为了方便驾驶，此时需要改变灯光信息；出现在驾驶过程中需要对驾驶环境参数进行调整的情况，驾驶员可直接通过人脸特征认证后对车内驾驶环境参数进行设置，设置后，通过车载设备对驾驶环境参数的设置信息进行采集，并基于该驾驶环境参数的设置信息对注册人脸特征对应的驾驶环境个性化设置信息进行更新操作，以获得使设置的驾驶环境个性化设置信息更符合驾驶员的需求。
在一个或多个可选的实施例中，本申请实施例方法还包括：
根据接收的管理指令对存储的驾驶环境个性化设置信息进行以下至少一个操作：删除、编辑、权限设置等。
本申请实施例中，可实现具有权限的管理人员通过管理指令对驾驶环境个性化设置信息进行操作，例如：车主将车辆中某一个驾驶员的注册人脸特征和驾驶环境个性化设置信息删除，或车主将某一个驾驶员的权限限制在仅能调节座椅状态等；通过对驾驶环境个性化设置信息的操作，实现了个性化权限管理。
在一个或多个可选的实施例中，注册人脸特征和驾驶环境个性化设置信息之间的对应关系存储在以下至少一个位置：移动应用端、服务器、车载设备等。
本实施例中，注册人脸特征的信息和关系可以存储在移动应用端、服务器或车载设备等位置，当存 储在移动应用端时，车机端与移动应用端相互通信，车机端获取驾驶员图像之后可以从移动应用端下载相应信息进行认证，或将人脸特征传输到移动应用端中进行认证，完成认证后移动应用端将驾驶环境个性化设置信息发送给车机端；当存储在车载设备中时，车机端无需与外界通信，直接将车载摄像头获得的驾驶员的人脸特征与车载设备存储的注册人脸特征进行认证即可；当存储在服务器时，需要服务器与车载设备相互通信，车机端获取驾驶员图像之后可以从服务器下载相应信息进行认证，或将人脸特征上传到服务器中进行认证，完成认证后服务器将驾驶环境个性化设置信息发送给车机端。
在一个或多个可选的实施例中，驾驶环境参数的设置信息包括：座椅状态信息；
步骤1230包括：
对驾驶员的图像进行检测，获得检测结果；
根据检测结果确定驾驶员的体型相关信息和/或人脸高度信息；
基于体型相关信息和/或人脸高度信息，确定驾驶员的座椅状态信息。
该实施例的方案与上述图4所示的驾驶环境智能调整方法的又一实施例中的方案相同，可认为上述图4所述的实施例中的描述都适用于本实施例，可参照理解，在此不再赘述。
可选地，检测结果包括人脸参考点坐标；
对驾驶员的图像进行检测，获得检测结果，包括：对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的人脸参考点坐标；
检测结果确定驾驶员的人脸高度信息，包括：将人脸参考点坐标从相机坐标系转换到车机坐标系；基于在车机坐标系下的人脸参考点坐标确定驾驶员的人脸高度信息。
该实施例的方案与上述驾驶环境智能调整方法中对应的实施例中的方案相同，可认为上述驾驶环境智能调整方法的对应实施例中的描述都适用于本实施例，可参照理解，在此不再赘述。
可选地，人脸参考点包括至少一个人脸关键点和/或至少一个人脸其他位置点；
对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的人脸参考点坐标，包括：
对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的至少一个人脸关键点坐标；
和/或，基于至少一个人脸关键点坐标确定至少一个人脸其他位置点。
该实施例的方案与上述驾驶环境智能调整方法中对应的实施例中的方案相同，可认为上述驾驶环境智能调整方法的对应实施例中的描述都适用于本实施例，可参照理解，在此不再赘述。
可选地，体型相关信息包括人种信息和/或性别信息；
对驾驶员的图像进行检测，获得检测结果，包括：
将驾驶员的图像输入用于属性检测的神经网络进行属性检测，得到神经网络输出的属性检测结果；
根据检测结果确定驾驶员的体型相关信息，包括：
基于属性检测结果获得图像对应的驾驶员的人种信息和/或性别信息。
该实施例的方案与上述驾驶环境智能调整方法中对应的实施例中的方案相同，可认为上述驾驶环境智能调整方法的对应实施例中的描述都适用于本实施例，可参照理解，在此不再赘述。
可选地，基于体型相关信息和/或人脸高度信息，确定驾驶员的座椅状态信息，包括：
获得预设的与体型和/或人脸高度相关的座椅调节转换关系；
基于体型相关信息和/或人脸高度信息、及座椅调节转换关系，确定驾驶员对应的座椅期望状态，将座椅期望状态作为驾驶员的座椅状态信息。
该实施例的方案与上述驾驶环境智能调整方法中对应的实施例中的方案相同，可认为上述驾驶环境智能调整方法的对应实施例中的描述都适用于本实施例，可参照理解，在此不再赘述。
可选地，基于体型相关信息和人脸高度信息，确定驾驶员的座椅状态信息，包括：
获得预设的与人脸高度相关的第一座椅调节转换关系；
基于人脸高度信息和第一座椅调节转换关系，确定驾驶员对应的第一座椅期望状态；
获得预设的与体型相关信息相关的第二座椅调节转换关系；
基于体型相关信息、第二座椅调节转换关系和第一座椅期望状态，确定第二座椅期望状态；
将第二座椅期望状态作为驾驶员的座椅状态信息。
该实施例的方案与上述驾驶环境智能调整方法中对应的实施例中的方案相同，可认为上述驾驶环境智能调整方法的对应实施例中的描述都适用于本实施例，可参照理解，在此不再赘述。
可选地，座椅的状态信息包括以下至少一个信息：座椅调节参数的目标值、座椅的上下位置信息、座椅的前后位置信息、座椅的左右位置信息、靠背椅倾斜角度的位置信息、坐垫倾斜角度的位置信息。
该实施例的方案与上述驾驶环境智能调整方法中对应的实施例中的方案相同，可认为上述驾驶环境智能调整方法的对应实施例中的描述都适用于本实施例，可参照理解，在此不再赘述。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
图13为本申请实施例提供的驾驶员注册装置的一个结构示意图。该实施例的装置可用于实现本申请上述各驾驶员注册方法实施例。如图13所示，该实施例的装置包括：
图像获取模块1301，用于获取驾驶员的图像,。
人脸特征提取模块1302，提取所述图像的人脸特征。
参数信息获取模块1303，获取驾驶环境参数的设置信息。
注册信息存储模块1304，将提取的人脸特征存储为注册人脸特征，将驾驶环境参数的设置信息存储为注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和驾驶环境个性化设置信息之间的对应关系。
本申请实施例为保证注册人脸特征与驾驶环境个性化设置信息一一对应，在存储时，还保存注册人脸特征和驾驶环境个性化设置信息之间的对应关系；在后续需要获取驾驶环境个性化设置信息时，只需进行人脸特征匹配即可通过对应关系获得对应的驾驶环境个性化设置信息，无需复杂的过程，基于人脸特征实现智能化的个性化配置，在保护驾驶员隐私的前提下实现了快速的驾驶环境个性化设置信息获取。
可选地，驾驶环境个性化设置信息包括以下至少之一：温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息等。
在一个或多个可选的实施例中，图像获取模块，用于通过移动应用端和/或车载摄像头获取驾驶员的图像。
可选地，图像获取模块，用于通过从移动应用端存储的至少一个图像中获取驾驶员的图像，或通过移动应用端设置的摄像装置采集获得驾驶员的图像。
在一个或多个可选的实施例中，参数信息获取模块1303，用于通过移动应用端和/或车载设备接收驾驶环境参数的设置信息。
可选地，参数信息获取模块1303，用于通过车载设备采集车辆中的驾驶环境参数的设置信息。
可选地，参数信息获取模块1303，用于通过车载设备采集车辆中的驾驶环境参数的设置信息；基于采集的驾驶环境参数的设置信息对注册人脸特征对应的驾驶环境个性化设置信息进行更新操作。
在一个或多个可选的实施例中，本申请实施例装置还包括：
信息管理模块，用于根据接收的管理指令对存储的驾驶环境个性化设置信息进行以下至少一个操作：删除、编辑、权限设置等。
在一个或多个可选的实施例中，注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系存储在以下至少一个位置：移动应用端、服务器、车载设备等。
在一个或多个可选的实施例中，驾驶环境参数的设置信息包括：座椅状态信息；
参数信息获取模块，用于对驾驶员的图像进行检测，获得检测结果；根据检测结果确定驾驶员的体型相关信息和/或人脸高度信息；基于体型相关信息和/或人脸高度信息，确定驾驶员的座椅状态信息。
在一个或多个可选的实施例中，检测结果包括人脸参考点坐标；
参数信息获取模块在对驾驶员的图像进行检测，获得检测结果时，用于对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的人脸参考点坐标；
参数信息获取模块在检测结果确定驾驶员的人脸高度信息时，用于将人脸参考点坐标从相机坐标系转换到车机坐标系；
基于在车机坐标系下的人脸参考点坐标确定驾驶员的人脸高度信息。
可选地，人脸参考点包括至少一个人脸关键点和/或至少一个人脸其他位置点；
参数信息获取模块在对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的人脸参考点坐标时，用于对驾驶员的图像进行人脸参考点检测，获得驾驶员在相机坐标系下的至少一个人脸关键点坐标；和/或，基于至少一个人脸关键点坐标确定至少一个人脸其他位置点。
可选地，体型相关信息包括人种信息和/或性别信息；
参数信息获取模块在对驾驶员的图像进行检测，获得检测结果时，用于将驾驶员的图像输入用于属性检测的神经网络进行属性检测，得到神经网络输出的属性检测结果；
参数信息获取模块在根据检测结果确定驾驶员的体型相关信息时，用于基于属性检测结果获得图像对应的驾驶员的人种信息和/或性别信息。
可选地，参数信息获取模块在基于体型相关信息和/或人脸高度信息，确定驾驶员的座椅状态信息时，用于获得预设的与体型和/或人脸高度相关的座椅调节转换关系；基于体型相关信息和/或人脸高度信息和座椅调节转换关系，确定驾驶员对应的座椅期望状态，将座椅期望状态作为驾驶员的座椅状态信息。
可选地，参数信息获取模块在基于体型相关信息和人脸高度信息，确定驾驶员的座椅状态信息时，用于获得预设的与人脸高度相关的第一座椅调节转换关系；基于人脸高度信息和第一座椅调节转换关系，确定驾驶员对应的第一座椅期望状态；获得预设的与体型相关信息相关的第二座椅调节转换关系；基于体型相关信息、第二座椅调节转换关系和第一座椅期望状态，确定第二座椅期望状态；将第二座椅期望状态作为驾驶员的座椅状态信息。
可选地，座椅的状态信息包括以下至少一个信息：座椅调节参数的目标值、座椅的上下位置信息、座椅的前后位置信息、座椅的左右位置信息、靠背椅倾斜角度的位置信息、坐垫倾斜角度的位置信息。
本公开实施例提供的驾驶员注册装置任一实施例的工作过程、设置方式及相应技术效果，均可以参照本公开上述相应方法实施例的具体描述，限于篇幅，在此不再赘述。
根据本申请实施例的另一个方面，提供的一种车辆，包括：如上述任意一项实施例提供的驾驶环境智能调整装置或如上述任意一项实施例提供的驾驶员注册装置。
根据本申请实施例的又一个方面，提供的一种电子设备，包括处理器，该处理器包括上述任意一项实施例提供的驾驶环境智能调整装置或上述任意一项实施例提供的驾驶员注册装置。
根据本申请实施例的还一个方面，提供的一种电子设备，包括：存储器，用于存储可执行指令；
以及处理器，用于与存储器通信以执行该可执行指令从而完成上述任意一项实施例提供的驾驶环境智能调整方法或上述任意一项实施例提供的驾驶员注册方法的操作。
根据本申请实施例的再一个方面，提供的一种计算机存储介质，用于存储计算机可读取的指令，该指令被执行时执行上述任意一项实施例提供的驾驶环境智能调整方法或上述任意一项实施例提供的驾驶员注册方法的操作。
本申请各实施例中的神经网络，分别可以是一个多层神经网络(即：深度神经网络)，例如多层的卷积神经网络，例如可以是LeNet、AlexNet、GoogLeNet、VGG、ResNet等任意神经网络模型。各神经网络可以采用相同类型和结构的神经网络，也可以采用不同类型和结构的神经网络。本申请实施例不对此进行限制。
本申请实施例还提供了一种电子设备，例如可以是移动终端、个人计算机(PC)、平板电脑、服务器等。下面参考图14，其示出了适于用来实现本申请实施例的终端设备或服务器的电子设备1400的结构示意图：如图14所示，电子设备1400包括一个或多个处理器、通信部等，所述一个或多个处理器例如：一个或多个中央处理单元(CPU)1401，和/或一个或多个专用处理器，专用处理器可作为加速单元1413，可包括但不限于图像处理器(GPU)、FPGA、DSP以及其它的ASIC芯片之类专用处理器等，处理器可以根据存储在只读存储器(ROM)1402中的可执行指令或者从存储部分1408加载到随机访问存储器(RAM)1403中的可执行指令而执行各种适当的动作和处理。通信部1412可包括但不限于网卡，所述网卡可包括但不限于IB(Infiniband)网卡。
处理器可与只读存储器1402和/或随机访问存储器1403中通信以执行可执行指令，通过总线1404与通信部1412相连、并经通信部1412与其他目标设备通信，从而完成本申请实施例提供的任一项方法对应的操作，例如，提取车载摄像头采集的驾驶员的图像的人脸特征；基于预先存储的至少一注册人脸特征对提取的人脸特征进行认证；响应于人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，或者，根据驾驶环境个性化设置信息控制车辆进行驾驶环境的相应调整。
此外，在RAM 1403中，还可存储有装置操作所需的各种程序和数据。CPU1401、ROM1402以及RAM1403通过总线1404彼此相连。在有RAM1403的情况下，ROM1402为可选模块。RAM1403存储可执行指令，或在运行时向ROM1402中写入可执行指令，可执行指令使中央处理单元1401执行上述通信方法对应的操作。输入/输出(I/O)接口1405也连接至总线1404。通信部1412可以集成设置，也可以设置为具有多个子模块(例如多个IB网卡)，并在总线链接上。
以下部件连接至I/O接口1405：包括键盘、鼠标等的输入部分1406；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分1407；包括硬盘等的存储部分1408；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分1409。通信部分1409经由诸如因特网的网络执行通信处理。驱动器1410也根据需要连接至I/O接口1405。可拆卸介质1411，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器1410上，以便于从其上读出的计算机程序根据需要被安装入存储部分1408。
需要说明的，如图14所示的架构仅为一种可选实现方式，在具体实践过程中，可根据实际需要对上述图14的部件数量和类型进行选择、删减、增加或替换；在不同功能部件设置上，也可采用分离设置或集成设置等实现方式，例如加速单元1413和CPU1401可分离设置或者可将加速单元1413集成在CPU1401上，通信部可分离设置，也可集成设置在CPU1401或加速单元1413上，等等。这些可替换的实施方式均落入本申请公开的保护范围。
特别地，根据本申请的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本申请的实施例包括一种计算机程序产品，其包括有形地包含在机器可读介质上的计算机程序，计算机程序包含用于执行流程图所示的方法的程序代码，程序代码可包括对应执行本申请实施例提供的方法步骤对应的指令，例如，提取车载摄像头采集的驾驶员的图像的人脸特征；基于预先存储的至少一注册人脸特征对提取的人脸特征进行认证；响应于人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；向设置有车载摄像头的车辆发送驾驶环境个性化设置信息，或者，根据驾驶环境个性化设置信息控制车辆进行驾驶环境的相应调整。在这样的实施例中，该计算机程序可以通过通信部分1409从网络上被下载和安装，和/或从可拆卸介质1411被安装。在该计算机程序被中央处理单元(CPU)1401执行时，执行本申请的方法中限定的上述功能的操作。
本说明书中各个实施例均采用递进的方式描述，每个实施例重点说明的都是与其它实施例的不同之处，各个实施例之间相同或相似的部分相互参见即可。对于系统实施例而言，由于其与方法实施例基本对应，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。
可能以许多方式来实现本申请的方法和装置。例如，可通过软件、硬件、固件或者软件、硬件、固件的任何组合来实现本申请的方法和装置。用于所述方法的步骤的上述顺序仅是为了进行说明，本申请的方法的步骤不限于以上具体描述的顺序，除非以其它方式特别说明。此外，在一些实施例中，还可将本申请实施为记录在记录介质中的程序，这些程序包括用于实现根据本申请的方法的机器可读指令。因而，本申请还覆盖存储用于执行根据本申请的方法的程序的记录介质。
本申请的描述是为了示例和描述起见而给出的，而并不是无遗漏的或者将本申请限于所公开的形式。很多修改和变化对于本领域的普通技术人员而言是显然的。选择和描述实施例是为了更好说明本申请的原理和实际应用，并且使本领域的普通技术人员能够理解本申请从而设计适于特定用途的带有各种修改的各种实施例。

Claims (79)

  1. 一种驾驶环境智能调整方法，其特征在于，包括：
    提取车载摄像头采集的驾驶员的图像的人脸特征；
    基于预先存储的至少一注册人脸特征对提取的所述人脸特征进行认证；
    响应于所述人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与所述人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；
    向设置有所述车载摄像头的车辆发送所述驾驶环境个性化设置信息，或者，根据所述驾驶环境个性化设置信息控制所述车辆进行驾驶环境的相应调整。
  2. 根据权利要求1所述的方法，其特征在于，所述驾驶环境个性化设置信息包括以下至少之一：温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息。
  3. 根据权利要求1或2所述的方法，其特征在于，还包括：
    响应于所述人脸特征认证不通过，发出注册申请提示信息或者认证不通过提示信息。
  4. 根据权利要求1-3任一所述的方法，其特征在于，所述基于预先存储的至少一注册人脸特征对提取的所述人脸特征进行认证之前，还包括：
    通过驾驶员注册流程获取驾驶员的注册人脸特征、驾驶环境个性化设置信息以及二者之间的对应关系。
  5. 根据权利要求4所述的方法，其特征在于，所述驾驶员注册流程包括：
    获取驾驶员的图像；
    提取所述图像的人脸特征；
    获取驾驶环境参数的设置信息；
    将提取的人脸特征存储为注册人脸特征，将所述驾驶环境参数的设置信息存储为所述注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系。
  6. 根据权利要求5所述的方法，其特征在于，所述获取驾驶员的图像，包括：
    通过移动应用端和/或车载摄像头获取所述驾驶员的图像。
  7. 根据权利要求6所述的方法，其特征在于，所述通过移动应用端获取所述驾驶员的图像，包括：
    通过从所述移动应用端存储的至少一个图像中获取所述驾驶员的图像，或
    通过所述移动应用端设置的摄像装置采集获得所述驾驶员的图像。
  8. 根据权利要求5-7任一所述的方法，其特征在于，所述获取驾驶环境参数的设置信息，包括：
    通过移动应用端和/或车载设备接收所述驾驶环境参数的设置信息。
  9. 根据权利要求5-8任一所述的方法，其特征在于，所述获取驾驶环境参数的设置信息，包括：
    通过车载设备采集车辆中的所述驾驶环境参数的设置信息。
  10. 根据权利要求5-9任一所述的方法，其特征在于，所述获取驾驶环境参数的设置信息，包括：
    通过车载设备采集车辆中的所述驾驶环境参数的设置信息；
    基于所述采集的驾驶环境参数的设置信息对所述注册人脸特征对应的所述驾驶环境个性化设置信息进行更新操作。
  11. 根据权利要求5-10任一所述的方法，其特征在于，还包括：
    根据接收的管理指令对所述存储的驾驶环境个性化设置信息进行以下至少一个操作：删除、编辑、权限设置。
  12. 根据权利要求5-11任一所述的方法，其特征在于，所述注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系存储在以下至少一个位置：移动应用端、服务器、车载设备。
  13. 根据权利要求12所述的方法，其特征在于，所述向设置有所述车载摄像头的车辆发送所述驾驶环境个性化设置信息，包括：
    通过与所述车辆相通信的服务器或移动应用端向设置有所述车载摄像头的车辆发送所述驾驶环境个性化设置信息。
  14. 根据权利要求12所述的方法，其特征在于，所述根据所述驾驶环境个性化设置信息控制所述车辆进行驾驶环境的相应调整，包括：
    通过车载设备根据所述驾驶环境个性化设置信息对设置有所述车载摄像头的车辆进行驾驶环境的相应调整。
  15. 根据权利要求5-14任一所述的方法，其特征在于，所述驾驶环境参数的设置信息包括：座椅状态信息；
    所述获取驾驶环境参数的设置信息，包括：
    对所述驾驶员的图像进行检测，获得检测结果；
    根据所述检测结果确定所述驾驶员的体型相关信息和/或人脸高度信息；
    基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息。
  16. 根据权利要求15所述的方法，其特征在于，所述检测结果包括人脸参考点坐标；
    所述对驾驶员的图像进行检测，获得检测结果，包括：
    对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的人脸参考点坐标；
    所述检测结果确定所述驾驶员的人脸高度信息，包括：
    将所述人脸参考点坐标从所述相机坐标系转换到车机坐标系；
    基于在所述车机坐标系下的人脸参考点坐标确定所述驾驶员的人脸高度信息。
  17. 根据权利要求16所述的方法，其特征在于，所述人脸参考点包括至少一个人脸关键点和/或至少一个人脸其他位置点；
    所述对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的人脸参考点坐标，包括：
    对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的至少一个人脸关键点坐标；
    和/或，基于所述至少一个人脸关键点坐标确定至少一个人脸其他位置点。
  18. 根据权利要求15-17任一所述的方法，其特征在于，所述体型相关信息包括人种信息和/或性别信息；
    所述对驾驶员的图像进行检测，获得检测结果，包括：
    将所述驾驶员的图像输入用于属性检测的神经网络进行属性检测，得到神经网络输出的属性检测结果；
    所述根据所述检测结果确定所述驾驶员的体型相关信息，包括：
    基于所述属性检测结果获得所述图像对应的驾驶员的人种信息和/或性别信息。
  19. 根据权利要求15-18任一所述的方法，其特征在于，所述基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息，包括：
    获得预设的与体型和/或人脸高度相关的座椅调节转换关系；
    基于所述体型相关信息和/或所述人脸高度信息、及所述座椅调节转换关系，确定所述驾驶员对应的座椅期望状态，将所述座椅期望状态作为所述驾驶员的座椅状态信息。
  20. 根据权利要求15-18任一所述的方法，其特征在于，所述基于所述体型相关信息和所述人脸高度信息，确定所述驾驶员的座椅状态信息，包括：
    获得预设的与人脸高度相关的第一座椅调节转换关系；
    基于所述人脸高度信息和所述第一座椅调节转换关系，确定所述驾驶员对应的第一座椅期望状态；
    获得预设的与体型相关信息相关的第二座椅调节转换关系；
    基于所述体型相关信息、所述第二座椅调节转换关系和所述第一座椅期望状态，确定第二座椅期望状态；
    将所述第二座椅期望状态作为所述驾驶员的座椅状态信息。
  21. 根据权利要求15-20任一所述的方法，其特征在于，所述座椅的状态信息包括以下至少一个信息：座椅调节参数的目标值、座椅的上下位置信息、座椅的前后位置信息、座椅的左右位置信息、靠背 椅倾斜角度的位置信息、坐垫倾斜角度的位置信息。
  22. 一种驾驶员注册方法，其特征在于，包括：
    获取驾驶员的图像；
    提取所述图像的人脸特征；
    获取驾驶环境参数的设置信息；
    将提取的人脸特征存储为注册人脸特征，将所述驾驶环境参数的设置信息存储为所述注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系。
  23. 根据权利要求22所述的方法，其特征在于，所述驾驶环境个性化设置信息包括以下至少之一：温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息。
  24. 根据权利要求22或23所述的方法，其特征在于，所述获取驾驶员的图像，包括：
    通过移动应用端和/或车载摄像头获取所述驾驶员的图像。
  25. 根据权利要求24所述的方法，其特征在于，所述通过移动应用端获取所述驾驶员的图像，包括：
    通过从所述移动应用端存储的至少一个图像中获取所述驾驶员的图像，或
    通过所述移动应用端设置的摄像装置采集获得所述驾驶员的图像。
  26. 根据权利要求22-25所述的方法，其特征在于，所述获取驾驶环境参数的设置信息，包括：
    通过移动应用端和/或车载设备接收所述驾驶环境参数的设置信息。
  27. 根据权利要求22-26所述的方法，其特征在于，所述获取驾驶环境参数的设置信息，包括：
    通过车载设备采集车辆中的所述驾驶环境参数的设置信息。
  28. 根据权利要求22-27所述的方法，其特征在于，所述获取驾驶环境参数的设置信息，包括：
    通过车载设备采集车辆中的所述驾驶环境参数的设置信息；
    基于所述采集的驾驶环境参数的设置信息对所述注册人脸特征对应的所述驾驶环境个性化设置信息进行更新操作。
  29. 根据权利要求22-28任一所述的方法，其特征在于，还包括：
    根据接收的管理指令对所述存储的驾驶环境个性化设置信息进行以下至少一个操作：删除、编辑、权限设置。
  30. 根据权利要求22-29任一所述的方法，其特征在于，所述注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系存储在以下至少一个位置：移动应用端、服务器、车载设备。
  31. 根据权利要求22-30任一所述的方法，其特征在于，所述驾驶环境参数的设置信息包括：座椅状态信息；
    所述获取驾驶环境参数的设置信息，包括：
    对所述驾驶员的图像进行检测，获得检测结果；
    根据所述检测结果确定所述驾驶员的体型相关信息和/或人脸高度信息；
    基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息。
  32. 根据权利要求31所述的方法，其特征在于，所述检测结果包括人脸参考点坐标；
    所述对驾驶员的图像进行检测，获得检测结果，包括：
    对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的人脸参考点坐标；
    所述检测结果确定所述驾驶员的人脸高度信息，包括：
    将所述人脸参考点坐标从所述相机坐标系转换到车机坐标系；
    基于在所述车机坐标系下的人脸参考点坐标确定所述驾驶员的人脸高度信息。
  33. 根据权利要求32所述的方法，其特征在于，所述人脸参考点包括至少一个人脸关键点和/或至少一个人脸其他位置点；
    所述对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的人脸参考点坐标，包括：
    对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的至少一个人脸关键点 坐标；
    和/或，基于所述至少一个人脸关键点坐标确定至少一个人脸其他位置点。
  34. 根据权利要求31-33任一所述的方法，其特征在于，所述体型相关信息包括人种信息和/或性别信息；
    所述对驾驶员的图像进行检测，获得检测结果，包括：
    将所述驾驶员的图像输入用于属性检测的神经网络进行属性检测，得到神经网络输出的属性检测结果；
    所述根据所述检测结果确定所述驾驶员的体型相关信息，包括：
    基于所述属性检测结果获得所述图像对应的驾驶员的人种信息和/或性别信息。
  35. 根据权利要求31-34任一所述的方法，其特征在于，所述基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息，包括：
    获得预设的与体型和/或人脸高度相关的座椅调节转换关系；
    基于所述体型相关信息和/或所述人脸高度信息、及所述座椅调节转换关系，确定所述驾驶员对应的座椅期望状态，将所述座椅期望状态作为所述驾驶员的座椅状态信息。
  36. 根据权利要求31-34任一所述的方法，其特征在于，所述基于所述体型相关信息和所述人脸高度信息，确定所述驾驶员的座椅状态信息，包括：
    获得预设的与人脸高度相关的第一座椅调节转换关系；
    基于所述人脸高度信息和所述第一座椅调节转换关系，确定所述驾驶员对应的第一座椅期望状态；
    获得预设的与体型相关信息相关的第二座椅调节转换关系；
    基于所述体型相关信息、所述第二座椅调节转换关系和所述第一座椅期望状态，确定第二座椅期望状态；
    将所述第二座椅期望状态作为所述驾驶员的座椅状态信息。
  37. 根据权利要求31-36任一所述的方法，其特征在于，所述座椅的状态信息包括以下至少一个信息：座椅调节参数的目标值、座椅的上下位置信息、座椅的前后位置信息、座椅的左右位置信息、靠背椅倾斜角度的位置信息、坐垫倾斜角度的位置信息。
  38. 一种驾驶环境智能调整装置，其特征在于，包括：
    特征提取单元，用于提取车载摄像头采集的驾驶员的图像的人脸特征；
    人脸特征认证单元，用于基于预先存储的至少一注册人脸特征对提取的所述人脸特征进行认证；
    环境信息获取单元，用于响应于所述人脸特征认证通过，根据预先存储的注册人脸特征与驾驶环境个性化设置信息之间的对应关系，确定与所述人脸特征对应的注册人脸特征所对应的驾驶环境个性化设置信息；
    信息处理单元，用于向设置有所述车载摄像头的车辆发送所述驾驶环境个性化设置信息，或者，根据所述驾驶环境个性化设置信息控制所述车辆进行驾驶环境的相应调整。
  39. 根据权利要求38所述的装置，其特征在于，所述驾驶环境个性化设置信息包括以下至少之一：温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息。
  40. 根据权利要求38或39所述的装置，其特征在于，所述装置还包括：
    提示信息单元，用于响应于所述人脸特征认证不通过，发出注册申请提示信息或者认证不通过提示信息。
  41. 根据权利要求38-40任一所述的装置，其特征在于，所述装置还包括：
    驾驶员注册单元，用于通过驾驶员注册流程获取驾驶员的注册人脸特征、驾驶环境个性化设置信息以及二者之间的对应关系。
  42. 根据权利要求41所述的装置，其特征在于，所述驾驶员注册单元，包括：
    图像获取模块，用于获取驾驶员的图像；
    人脸特征提取模块，用于提取所述图像的人脸特征；
    参数信息获取模块，用于获取驾驶环境参数的设置信息；
    注册信息存储模块，用于将提取的人脸特征存储为注册人脸特征，将所述驾驶环境参数的设置信息存储为所述注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系。
  43. 根据权利要求42所述的装置，其特征在于，所述图像获取模块，用于通过移动应用端和/或车载摄像头获取所述驾驶员的图像。
  44. 根据权利要求43所述的装置，其特征在于，所述图像获取模块，用于通过从所述移动应用端存储的至少一个图像中获取所述驾驶员的图像，或通过所述移动应用端设置的摄像装置采集获得所述驾驶员的图像。
  45. 根据权利要求42-44任一所述的装置，其特征在于，所述参数信息获取模块，用于通过移动应用端和/或车载设备接收所述驾驶环境参数的设置信息。
  46. 根据权利要求42-45任一所述的装置，其特征在于，所述参数信息获取模块，用于通过车载设备采集车辆中的所述驾驶环境参数的设置信息。
  47. 根据权利要求42-46任一所述的装置，其特征在于，所述参数信息获取模块，用于通过车载设备采集车辆中的所述驾驶环境参数的设置信息；基于所述采集的驾驶环境参数的设置信息对所述注册人脸特征对应的所述驾驶环境个性化设置信息进行更新操作。
  48. 根据权利要求42-47任一所述的装置，其特征在于，所述驾驶员注册单元，还包括：
    信息管理模块，用于根据接收的管理指令对所述存储的驾驶环境个性化设置信息进行以下至少一个操作：删除、编辑、权限设置。
  49. 根据权利要求42-48任一所述的装置，其特征在于，所述注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系存储在以下至少一个位置：移动应用端、服务器、车载设备。
  50. 根据权利要求49所述的装置，其特征在于，所述信息处理单元在向设置有所述车载摄像头的车辆发送所述驾驶环境个性化设置信息时，用于通过与所述车辆相通信的服务器或移动应用端向所述驾驶员所在的车辆发送所述驾驶环境个性化设置信息。
  51. 根据权利要求49所述的装置，其特征在于，所述信息处理单元在根据所述驾驶环境个性化设置信息控制所述车辆进行驾驶环境的相应调整时，用于通过车载设备根据所述驾驶环境个性化设置信息对设置有所述车载摄像头的车辆进行驾驶环境的相应调整。
  52. 根据权利要求42-51任一所述的装置，其特征在于，所述驾驶环境参数的设置信息包括：座椅状态信息；
    所述参数信息获取模块，用于对所述驾驶员的图像进行检测，获得检测结果；根据所述检测结果确定所述驾驶员的体型相关信息和/或人脸高度信息；基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息。
  53. 根据权利要求52所述的装置，其特征在于，所述检测结果包括人脸参考点坐标；
    所述参数信息获取模块在对驾驶员的图像进行检测，获得检测结果时，用于对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的人脸参考点坐标；
    所述参数信息获取模块在检测结果确定所述驾驶员的人脸高度信息时，用于将所述人脸参考点坐标从所述相机坐标系转换到车机坐标系；基于在所述车机坐标系下的人脸参考点坐标确定所述驾驶员的人脸高度信息。
  54. 根据权利要求53所述的装置，其特征在于，所述人脸参考点包括至少一个人脸关键点和/或至少一个人脸其他位置点；
    所述参数信息获取模块在对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的人脸参考点坐标时，用于对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的至少一个人脸关键点坐标；和/或，基于所述至少一个人脸关键点坐标确定至少一个人脸其他位置点。
  55. 根据权利要求52-54任一所述的装置，其特征在于，所述体型相关信息包括人种信息和/或性别信息；
    所述参数信息获取模块在对驾驶员的图像进行检测，获得检测结果时，用于将所述驾驶员的图像输入用于属性检测的神经网络进行属性检测，得到神经网络输出的属性检测结果；
    所述参数信息获取模块在根据所述检测结果确定所述驾驶员的体型相关信息时，用于基于所述属性检测结果获得所述图像对应的驾驶员的人种信息和/或性别信息。
  56. 根据权利要求52-55任一所述的装置，其特征在于，所述参数信息获取模块在基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息时，用于获得预设的与体型和/或人脸高度相关的座椅调节转换关系；基于所述体型相关信息和/或所述人脸高度信息、及所述座椅调节转换关系，确定所述驾驶员对应的座椅期望状态，将所述座椅期望状态作为所述驾驶员的座椅状态信息。
  57. 根据权利要求52-55任一所述的装置，其特征在于，所述参数信息获取模块在基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息时，用于获得预设的与人脸高度相关的第一座椅调节转换关系；基于所述人脸高度信息和所述第一座椅调节转换关系，确定所述驾驶员对应的第一座椅期望状态；获得预设的与体型相关信息相关的第二座椅调节转换关系；基于所述体型相关信息、所述第二座椅调节转换关系和所述第一座椅期望状态，确定第二座椅期望状态；将所述第二座椅期望状态作为所述驾驶员的座椅状态信息。
  58. 根据权利要求52-57任一所述的装置，其特征在于，所述座椅的状态信息包括以下至少一个信息：座椅调节参数的目标值、座椅的上下位置信息、座椅的前后位置信息、座椅的左右位置信息、靠背椅倾斜角度的位置信息、坐垫倾斜角度的位置信息。
  59. 一种驾驶员注册装置，其特征在于，包括：
    图像获取模块，用于获取驾驶员的图像；
    人脸特征提取模块，提取所述图像的人脸特征；
    参数信息获取模块，获取驾驶环境参数的设置信息；
    注册信息存储模块，将提取的人脸特征存储为注册人脸特征，将所述驾驶环境参数的设置信息存储为所述注册人脸特征的驾驶环境个性化设置信息，建立并存储注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系。
  60. 根据权利要求59所述的装置，其特征在于，所述驾驶环境个性化设置信息包括以下至少之一：温度信息、灯光信息、音乐风格信息、座椅状态信息、音响设置信息。
  61. 根据权利要求59或60所述的装置，其特征在于，所述图像获取模块，用于通过移动应用端和/或车载摄像头获取所述驾驶员的图像。
  62. 根据权利要求61所述的装置，其特征在于，所述图像获取模块，用于通过从所述移动应用端存储的至少一个图像中获取所述驾驶员的图像，或通过所述移动应用端设置的摄像装置采集获得所述驾驶员的图像。
  63. 根据权利要求59-62所述的装置，其特征在于，所述参数信息获取模块，用于通过移动应用端和/或车载设备接收所述驾驶环境参数的设置信息。
  64. 根据权利要求59-63所述的装置，其特征在于，所述参数信息获取模块，用于通过车载设备采集车辆中的所述驾驶环境参数的设置信息。
  65. 根据权利要求59-64所述的装置，其特征在于，所述参数信息获取模块，用于通过车载设备采集车辆中的所述驾驶环境参数的设置信息；基于所述采集的驾驶环境参数的设置信息对所述注册人脸特征对应的所述驾驶环境个性化设置信息进行更新操作。
  66. 根据权利要求59-65任一所述的装置，其特征在于，所述装置还包括：
    信息管理模块，用于根据接收的管理指令对所述存储的驾驶环境个性化设置信息进行以下至少一个操作：删除、编辑、权限设置。
  67. 根据权利要求59-66任一所述的装置，其特征在于，所述注册人脸特征和所述驾驶环境个性化设置信息之间的对应关系存储在以下至少一个位置：移动应用端、服务器、车载设备。
  68. 根据权利要求59-67任一所述的装置，其特征在于，所述驾驶环境参数的设置信息包括：座椅状态信息；
    所述参数信息获取模块，用于对所述驾驶员的图像进行检测，获得检测结果；根据所述检测结果确定所述驾驶员的体型相关信息和/或人脸高度信息；基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息。
  69. 根据权利要求68所述的装置，其特征在于，所述检测结果包括人脸参考点坐标；
    所述参数信息获取模块在对驾驶员的图像进行检测，获得检测结果时，用于对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的人脸参考点坐标；
    所述参数信息获取模块在检测结果确定所述驾驶员的人脸高度信息时，用于将所述人脸参考点坐标从所述相机坐标系转换到车机坐标系；
    基于在所述车机坐标系下的人脸参考点坐标确定所述驾驶员的人脸高度信息。
  70. 根据权利要求69所述的装置，其特征在于，所述人脸参考点包括至少一个人脸关键点和/或至少一个人脸其他位置点；
    所述参数信息获取模块在对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的人脸参考点坐标时，用于对所述驾驶员的图像进行人脸参考点检测，获得所述驾驶员在相机坐标系下的至少一个人脸关键点坐标；和/或，基于所述至少一个人脸关键点坐标确定至少一个人脸其他位置点。
  71. 根据权利要求68-70任一所述的装置，其特征在于，所述体型相关信息包括人种信息和/或性别信息；
    所述参数信息获取模块在对驾驶员的图像进行检测，获得检测结果时，用于将所述驾驶员的图像输入用于属性检测的神经网络进行属性检测，得到神经网络输出的属性检测结果；
    所述参数信息获取模块在根据所述检测结果确定所述驾驶员的体型相关信息时，用于基于所述属性检测结果获得所述图像对应的驾驶员的人种信息和/或性别信息。
  72. 根据权利要求68-71任一所述的装置，其特征在于，所述参数信息获取模块在基于所述体型相关信息和/或所述人脸高度信息，确定所述驾驶员的座椅状态信息时，用于获得预设的与体型和/或人脸高度相关的座椅调节转换关系；基于所述体型相关信息和/或所述人脸高度信息、及所述座椅调节转换关系，确定所述驾驶员对应的座椅期望状态，将所述座椅期望状态作为所述驾驶员的座椅状态信息。
  73. 根据权利要求68-71任一所述的装置，其特征在于，所述参数信息获取模块在基于所述体型相关信息和所述人脸高度信息，确定所述驾驶员的座椅状态信息时，用于获得预设的与人脸高度相关的第一座椅调节转换关系；基于所述人脸高度信息和所述第一座椅调节转换关系，确定所述驾驶员对应的第一座椅期望状态；获得预设的与体型相关信息相关的第二座椅调节转换关系；基于所述体型相关信息、所述第二座椅调节转换关系和所述第一座椅期望状态，确定第二座椅期望状态；将所述第二座椅期望状态作为所述驾驶员的座椅状态信息。
  74. 根据权利要求68-73任一所述的装置，其特征在于，所述座椅的状态信息包括以下至少一个信息：座椅调节参数的目标值、座椅的上下位置信息、座椅的前后位置信息、座椅的左右位置信息、靠背椅倾斜角度的位置信息、坐垫倾斜角度的位置信息。
  75. 一种车辆，其特征在于，包括：权利要求38至58任意一项所述的驾驶环境智能调整装置或权利要求59至74任意一项所述的驾驶员注册装置。
  76. 一种电子设备，其特征在于，包括处理器，所述处理器包括权利要求38至58任意一项所述的驾驶环境智能调整装置或如权利要求59至74任意一项所述的驾驶员注册装置。
  77. 一种电子设备，其特征在于，包括：存储器，用于存储可执行指令；
    以及处理器，用于与所述存储器通信以执行所述可执行指令从而完成权利要求1至21任意一项所述驾驶环境智能调整方法或权利要求22至37任意一项所述的驾驶员注册方法。
  78. 一种计算机存储介质，用于存储计算机可读取的指令，其特征在于，所述指令被执行时执行权利要求1至21任意一项所述驾驶环境智能调整方法或权利要求22至37任意一项所述的驾驶员注册方法的操作。
  79. 一种计算机程序产品，包括计算机可读代码，其特征在于，当所述计算机可读代码在设备上运 行时，所述设备中的处理器执行用于实现权利要求1至21任意一项所述驾驶环境智能调整方法或权利要求22至37任意一项所述的驾驶员注册方法的指令。
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