CN116061878A - Vehicle keyless entry and starting method, device and storage medium - Google Patents
Vehicle keyless entry and starting method, device and storage medium Download PDFInfo
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- 230000008569 process Effects 0.000 claims description 9
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
- G06V10/12—Details of acquisition arrangements; Constructional details thereof
- G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
- G06V10/143—Sensing or illuminating at different wavelengths
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- 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
- G06V40/161—Detection; Localisation; Normalisation
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- G—PHYSICS
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- 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
- G06V40/172—Classification, e.g. identification
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/40—Spoof detection, e.g. liveness detection
- G06V40/45—Detection of the body part being alive
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
- G07C9/00563—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys using personal physical data of the operator, e.g. finger prints, retinal images, voicepatterns
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Abstract
The invention discloses a keyless entry and starting method of a vehicle, which comprises the following steps: acquiring first depth image information of a person approaching a vehicle door, and performing face detection processing on the first depth image information; performing living body detection processing on the first depth image information according to a face detection processing result, and performing identity verification processing on the first depth image information according to the living body detection processing result; controlling whether the vehicle door is unlocked or not according to the authentication processing result; after the vehicle door is unlocked, second depth image information of a driver of the vehicle is obtained, and face recognition verification processing is carried out on the second depth image information; and controlling whether the vehicle is started or not according to the face recognition verification processing result. A device and a storage medium for implementing the vehicle keyless entry and start method are also disclosed. The invention improves the convenience and safety of unlocking and starting the vehicle.
Description
Technical Field
The invention relates to the technical field of vehicle identification methods, in particular to a vehicle keyless entry and starting method and device based on face recognition and a storage medium.
Background
With the continuous development of automobile technology and the continuous increase of the quantity of maintenance, the demands of people for intelligent programs of automobiles are also continuously increasing. In addition to the need for driving and riding comfort of a car, whether a car is equipped with an intelligent device is one of the important considerations when purchasing a car.
Keyless entry systems have become a common configuration for modern automobiles, providing convenience to the vehicle owners to a certain extent, and also presenting certain security issues. Most of the existing keyless entry systems for vehicles mainly utilize dual radio frequency system matching between a vehicle key and a vehicle, and still require a vehicle owner to carry the vehicle key, and only the action of taking out the vehicle key to unlock can be omitted. The keyless entry system for vehicles generally only verifies the legitimacy of the vehicle key, but does not have the function of identifying and verifying the identity of the vehicle owner. When the car key is lost, if the car key is picked up by others, the car key can be unlocked and enter the car as well as the others. In actual life, there is a situation that a car key is forgotten to be carried or lost or is inconvenient to be carried, and a car needs to be accessed and started. Therefore, the drawbacks of the existing keyless entry systems for vehicles are revealed.
For this purpose, the applicant has found, through a beneficial search and study, a solution to the above-mentioned problems, against which the technical solutions to be described below are developed.
Disclosure of Invention
One of the technical problems to be solved by the invention is as follows: aiming at the defects of the prior art, the vehicle keyless entry and starting method based on face recognition improves the convenience and safety of vehicle unlocking and starting.
The second technical problem to be solved by the invention is that: a device for realizing the keyless entry and starting method of the vehicle is provided.
The third technical problem to be solved by the invention is as follows: a storage medium is provided that implements the above-described vehicle keyless entry and start method.
A vehicle keyless entry and starting method as a first aspect of the present invention includes:
acquiring first depth image information of a person approaching a vehicle door, and performing face detection processing on the first depth image information;
performing living body detection processing on the first depth image information according to a face detection processing result, and performing identity verification processing on the first depth image information according to the living body detection processing result;
controlling whether the vehicle door is unlocked or not according to the authentication processing result;
after the vehicle door is unlocked, second depth image information of a driver of the vehicle is obtained, and face recognition verification processing is carried out on the second depth image information; and
and controlling whether the vehicle is started or not according to the face recognition verification processing result.
In a preferred embodiment of the present invention, the acquiring the first depth image information of the person approaching the vehicle door includes:
when the vehicle is in a parking and door locking state, acquiring depth image information outside the vehicle door at a standby acquisition frame rate through a first TOF camera installed at the vehicle door;
detecting the acquired depth image information to judge whether a person approaches the vehicle door; and
and if the person is detected to be close to the vehicle door, the first TOF camera performs image acquisition processing on the person close to the vehicle door at a work acquisition frame rate so as to acquire first depth image information of the person close to the vehicle door.
In a preferred embodiment of the invention, the first depth image information comprises a depth image and a near infrared image.
In a preferred embodiment of the present invention, the performing face detection processing on the first depth image information includes:
acquiring a near infrared image in the first depth image information, and sending the near infrared image into a face detection module for face detection; and
judging whether a human face exists in the near infrared image according to a human face detection processing result, if the human face is detected, performing living body detection processing and identity verification processing, if the human face is not detected, continuing to perform image acquisition on a person approaching a vehicle door through the first TOF camera at a work acquisition frame rate and performing human face detection processing again, and if the person is detected to leave, adjusting the acquisition frame rate of the first TOF camera to be a standby acquisition frame rate.
In a preferred embodiment of the present invention, the performing the living body detection processing on the first depth image information according to the face detection processing result includes:
if the face detection processing result is that the face is detected, respectively performing image adjustment processing on the depth image and the near infrared image in the first depth image information;
carrying out gradient image processing on the depth image subjected to image adjustment processing to obtain gradient images in the horizontal direction, the vertical direction and the center-to-edge direction of the depth image, and combining the three gradient images into a three-channel depth image;
combining the depth image subjected to image adjustment processing with the near infrared image to obtain a three-channel gray level image;
sending the three-channel depth image into a living body detection model based on the depth image to calculate a depth image model score;
if the depth image model score is higher than a first living body threshold value, the three-channel gray level image is sent into a living body detection model based on a near infrared image to calculate a gray level image model score;
if the gray image model score is higher than a second living body threshold value, the three-channel depth image and the three-channel gray image are correspondingly placed into a depth image cache queue and a gray image cache queue;
repeatedly calculating model scores until the queue lengths of the depth image cache queue and the gray image cache queue are equal to preset values, respectively taking out three-channel depth images and three-channel gray images from the depth image cache queue and the gray image cache queue, and respectively emptying the depth image cache queue and the gray image cache queue;
respectively calculating LBP-TOP characteristics of the three-channel depth image and the three-channel gray image, splicing the LBP-TOP characteristics of the three-channel depth image and the three-channel gray image, and then putting the three-channel depth image and the three-channel gray image into a time sequence living body detection model based on comprehensive characteristics to calculate a time sequence model score; and
and if the time sequence model score is larger than a third living body threshold value, the time sequence model score is determined to be living body.
In a preferred embodiment of the present invention, the performing image adjustment processing on the depth image and the near infrared image in the first depth image information includes:
respectively carrying out orthodontic adjustment treatment on the depth image and the near infrared image;
respectively carrying out filtering treatment on the depth image and the near infrared image which are subjected to orthodontic adjustment treatment;
respectively carrying out dynamic compression processing on the depth image and the near infrared image which are subjected to filtering processing; and
and respectively carrying out gray value normalization processing on the depth image and the near infrared image which are subjected to dynamic compression processing.
In a preferred embodiment of the present invention, the performing authentication processing on the first depth image information according to the living body detection processing result includes:
if the living body detection processing result is determined to be a living body, acquiring a near infrared image in the first depth image information; and
and comparing the near infrared image with an identity library of the local authorized unlocking vehicle, and unlocking the vehicle door if the comparison is passed.
In a preferred embodiment of the present invention, the acquiring second depth image information of a driver of the vehicle and performing face recognition verification processing on the second depth image information includes:
when the vehicle door is unlocked, acquiring depth image information outside the vehicle driving position at a standby acquisition frame rate through a second TOF camera installed at the vehicle driving position;
detecting the acquired depth image information to judge whether a person sits on a driver seat of the vehicle;
if the person is detected to be sitting on the vehicle driver seat, the second TOF camera is used for carrying out image acquisition processing on the vehicle driver seat person at a work acquisition frame rate so as to acquire second depth image information of the vehicle driver seat person;
sending the near infrared image in the second depth image information to a face detection module for face detection; and
judging whether a human face exists or not according to the human face detection processing result, if the human face is detected, comparing the near infrared image with an identity library of a local authorized starting vehicle, and if the comparison is passed, authorizing starting of the vehicle.
A vehicle keyless entry and starting device as a second aspect of the present invention includes:
a first TOF camera mounted at the door for acquiring first depth image information of a person approaching the door;
the second TOF camera is arranged at the vehicle driving position and is used for acquiring second depth image information of a person of the vehicle driving position;
the first depth image information processing module is used for acquiring first depth image information of a person approaching the vehicle door and carrying out face detection processing on the first depth image information;
the living body detection and identity verification module is used for carrying out living body detection processing on the first depth image information according to a human face detection processing result and carrying out identity verification processing on the first depth image information according to the living body detection processing result;
the door lock control module is used for controlling whether the door is unlocked or not according to the authentication processing result;
the second depth image information processing module is used for acquiring second depth image information of a vehicle driver after the vehicle door is unlocked and performing face recognition verification processing on the second depth image information; and
and the vehicle starting control module is used for controlling whether the vehicle is started or not according to the face recognition verification processing result.
A storage medium, which is a third invention of the present invention, is a storage medium that implements the above-described vehicle keyless entry and startup method, having stored thereon a program that, when executed by a processor, implements the steps of:
acquiring first depth image information of a person approaching a vehicle door, and performing face detection processing on the first depth image information;
performing living body detection processing on the first depth image information according to a face detection processing result, and performing identity verification processing on the first depth image information according to the living body detection processing result;
controlling whether the vehicle door is unlocked or not according to the authentication processing result;
after the vehicle door is unlocked, second depth image information of a driver of the vehicle is obtained, and face recognition verification processing is carried out on the second depth image information; and
and controlling whether the vehicle is started or not according to the face recognition verification processing result.
Due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. the invention collects the biological information of the user, verifies the biological characteristics of the user and authorizes the user to operate the vehicle, thereby realizing keyless entry and starting the automobile.
2. Compared with the traditional method for acquiring the human face by adopting a monocular or binocular sensor for living body detection, the method can acquire the depth map and the IR map by a single frame based on the TOF sensing technology, and has the advantages of small calculated amount and high real-time performance; meanwhile, the invention adopts the active light source, has less interference by the ambient light, can be used under complex ambient light conditions, has lower requirement on hardware, and is stable and reliable.
3. Compared with the scheme of the keyless entry system commonly adopted at present, the invention does not need a user to carry an entity key, has higher intelligentization degree, and can effectively prevent the key from being lost or not entering a vehicle when the key is not carried and prevent the property loss when the key is stolen.
4. Compared with the keyless entry system scheme based on fingerprint and other touch sensing technologies, the method has the advantages of living body identification and human face ID double verification, higher safety and no need of user cooperation and waiting.
5. Compared with a keyless entry system scheme for cloud identity verification, the invention provides a local offline identity information base, the information base can be set offline, all calculation is completed locally, the cloud is not required to be uploaded, the privacy security of a user is ensured, and the real-time performance is better.
6. Compared with the traditional keyless entry system, the face ID-based method has the advantages of less required hardware, low power consumption, low cost and low system complexity, and can bring lower failure rate and better experience for users.
7. Compared with the traditional vehicle starting logic, the invention provides the novel vehicle starting authorization verification logic, and unauthorized personnel cannot start the vehicle engine even if unlocking the vehicle, so that the vehicle can be effectively prevented from being started by children and other personnel by mistake, and the safety performance is further improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method of keyless entry and start-up of a vehicle of the present invention.
FIG. 2 is a flow chart of one embodiment of an application of the vehicle keyless entry and start method of the present invention.
Fig. 3 is a flowchart of an application embodiment of living body detection in the vehicle keyless entry and start method of the present invention.
Fig. 4 is a schematic structural view of the keyless entry and starting device for a vehicle of the present invention.
Detailed Description
The invention is further described with reference to the following detailed drawings in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the implementation of the invention easy to understand.
Referring to fig. 1, there is shown a vehicle keyless entry and start method comprising the steps of:
step S10, acquiring first depth image information of a person approaching a vehicle door, and performing face detection processing on the first depth image information;
step S20, performing living body detection processing on the first depth image information according to a face detection processing result, and performing identity verification processing on the first depth image information according to the living body detection processing result;
step S30, whether the vehicle door is unlocked or not is controlled according to the identity verification processing result;
step S40, after the vehicle door is unlocked, second depth image information of a driver of the vehicle is obtained, and face recognition verification processing is carried out on the second depth image information;
and step S50, controlling whether the vehicle is started or not according to the face recognition verification processing result.
Referring to fig. 1 in combination with fig. 2, in step S10, first depth image information of a person approaching a vehicle door is acquired, including the steps of:
step S11, when the vehicle is in a parking lock state, depth image information outside the door is acquired at a standby acquisition frame rate by a first TOF camera (image acquisition unit shown in fig. 2) mounted at the door. The frame rate of standby acquisition can be adaptively adjusted according to acquisition requirements;
step S12, detecting the acquired depth image information to judge whether a person approaches a vehicle door;
and step S13, if the fact that a person approaches the vehicle door is detected, performing image acquisition processing on the person approaching the vehicle door by the first TOF camera at a work acquisition frame rate so as to acquire first depth image information of the person approaching the vehicle door, wherein the first depth image information comprises a depth image and a near infrared image. The work acquisition frame rate can be adaptively adjusted according to acquisition requirements. The imaging principle of the near infrared image is that the first TOF camera adopts light with the active emission wavelength of 850nm or 940nm, and the light is processed into the near infrared image according to the light intensity of the reflected light.
Referring to fig. 1 in combination with fig. 2, in step S10, face detection processing is performed on the first depth image information, including the steps of:
step S14, acquiring a near infrared image in the first depth image information, and sending the near infrared image into a face detection module for face detection;
step S15, judging whether a human face exists in the near infrared image according to the human face detection processing result, if the human face is detected, entering a step S20 to carry out living body detection processing and identity verification processing, and if the human face is not detected, entering a step S16;
step S16, returning to the step S13, continuing to acquire images of persons approaching the vehicle door at a work acquisition frame rate through the first TOF camera and performing face detection again, and if the person is detected to leave, adjusting the acquisition frame rate of the first TOF camera to a standby acquisition frame rate.
Referring to fig. 3 in combination with fig. 1 and 2, in step S20, a living body detection process is performed on the first depth image information according to a face detection process result, including the steps of:
step S211, if the face detection processing result is that the face is detected, respectively performing image adjustment processing on the depth image and the near infrared image in the first depth image information;
step S212, carrying out gradient image processing on the depth image subjected to the image adjustment processing to obtain gradient images in the horizontal direction, the vertical direction and the center-to-edge direction of the depth image, and combining the three gradient images into a three-channel depth image D_IMG;
step S213, combining the depth image after the image adjustment processing with the near infrared image to obtain a three-channel gray level image I_IMG;
step S214, sending the three-channel depth image D_IMG into a living body detection MODEL D_MODEL based on the depth image to calculate a depth image MODEL score;
step S215, if the depth image MODEL score is higher than a first living body threshold S_D, the first living body threshold S_D is preset according to the MODEL requirement, the three-channel gray level image I_IMG is sent to a living body detection MODEL I_MODEL based on the near infrared image to calculate a gray level image MODEL score;
step S216, if the gray image model score is higher than a second living body threshold S_I, the second living body threshold S_I is preset according to the model requirement, the three-channel depth image D_IMG and the three-channel gray image I_IMG are correspondingly placed in a depth image cache queue Q_D and a gray image cache queue Q_I;
step S217, repeatedly calculating the model score (repeatedly executing steps S24 to S26) until the queue lengths of the depth image buffer queue q_d and the gray image buffer queue q_i are equal to the preset value, in this embodiment, the preset value is 3, which may be set to other values according to the model requirement; then three channels of depth images D_IMG and three channels of gray images I_IMG which are respectively taken out of the depth image cache queues Q_D and the gray image cache queues Q_I are respectively emptied, and meanwhile the depth image cache queues Q_D and the gray image cache queues Q_I are respectively emptied;
step S218, respectively calculating LBP-TOP characteristics (Local Binary Patterns from Three Orthogonal Planes) of the three-channel depth image D_IMG and the three-channel gray level image I_IMG, splicing the LBP-TOP characteristics of the three-channel depth image D_IMG and the three-channel gray level image I_IMG, and then putting the spliced LBP-TOP characteristics into a time sequence living body detection MODEL T_MODEL based on the comprehensive characteristics to calculate a time sequence MODEL score;
in step S219, if the time series model score is greater than the third living body threshold, the living body is determined, otherwise, the living body detection is not passed, and the process returns to step S217.
In step S211, image adjustment processing is performed on the depth image and the near infrared image in the first depth image information, respectively, including the steps of:
step S2111, respectively carrying out orthodontic adjustment processing on the depth image and the near infrared image;
step S2112, respectively carrying out filtering treatment on the depth image and the near infrared image which are subjected to orthodontic adjustment treatment;
in step S2113, the filtered depth image and the near infrared image are respectively dynamically compressed according to the pixel values, and in this embodiment, the depth image and the near infrared image are dynamically compressed to 8 bits. And setting the working condition distance as a depth range of interest according to the requirement, pulling up the depth value in the range, improving the contrast, and compressing the depth value outside the range. And searching maximum and minimum coordinates of pixel values on the corresponding near-infrared image according to the depth value pixel coordinates in the working condition range, dynamically adjusting the near-infrared image according to the maximum and minimum values searched by the coordinates, and compressing to 8 bits.
Step S2114, respectively performing gray value normalization processing on the depth image and the near infrared image subjected to dynamic compression processing.
In step S20, authentication processing is performed on the first depth image information according to the living body detection processing result, including the steps of:
step S221, if the living body detection processing result is determined as a living body, acquiring a near infrared image in the first depth image information;
step S221, the near infrared image is compared with an identity library of a local authorized unlocking vehicle, if the comparison is passed, the vehicle door is unlocked, and if the comparison is not passed, the step S10 is returned.
In step S40, second depth image information of a driver of the vehicle is acquired, and face recognition verification processing is performed on the second depth image information, including:
step S41, after the vehicle door is unlocked, acquiring depth image information outside the vehicle driving position at a standby acquisition frame rate through a second TOF camera installed at the vehicle driving position;
step S42, detecting the acquired depth image information to judge whether a person sits on a driver' S seat of the vehicle;
step S43, if a person is detected to be sitting on the vehicle driver seat, performing image acquisition processing on the vehicle driver seat person by using the second TOF camera at a work acquisition frame rate so as to acquire second depth image information of the vehicle driver seat person; if no person is detected to be sitting on the driver' S seat of the vehicle, returning to step S41;
step S44, the near infrared image in the second depth image information is sent to a face detection module for face detection;
step S45, judging whether a human face exists according to the human face detection processing result, if the human face is detected, entering step S46, and if the human face is not detected, returning to step S41;
step S46, comparing the near infrared image with an identity library of a local authorized starting vehicle; if the comparison is passed, authorizing starting the vehicle; if the comparison is not passed, the process returns to step S41.
In view of the inconvenience and potential safety hazard of the traditional keyless entry system, the invention collects the biological characteristics of the user through the depth sensor using TOF technology, carries out living body detection and ID identification verification on the user, and can enter the vehicle after the verification. If the ID verification of the driver's seat is passed, the vehicle is authorized to start. In addition, the invention provides a local identity information base for the user, and a vehicle owner can selectively input the identity base authorized to enter the vehicle and the identity base authorized to start the vehicle, thereby providing convenience for the family members to enter the vehicle and ensuring that the family members which are not authorized to start the vehicle, such as children, start the vehicle by mistake to cause safety accidents.
Referring to fig. 2, a vehicle keyless entry and start device is shown, which includes a first TOF camera 100, a second TOF camera 200, a first depth image information processing module 300, a living body detection and authentication module 400, a door lock control module 500, a second depth image information processing module 600, and a vehicle start control module 700.
A first TOF camera 100 is mounted at the door for acquiring first depth image information of a person approaching the door.
The second TOF camera 200 is mounted at the vehicle operator's seat for acquiring second depth image information of the vehicle operator.
The first depth image information processing module 300 is configured to acquire first depth image information of a person approaching the vehicle door, and perform face detection processing on the first depth image information.
The living body detection and authentication module 400 is configured to perform living body detection processing on the first depth image information according to the face detection processing result, and perform authentication processing on the first depth image information according to the living body detection processing result.
The door lock control module 500 is configured to control whether the door is unlocked according to the authentication processing result.
The second depth image information processing module 600 is configured to obtain second depth image information of a driver of the vehicle after the door is unlocked, and perform face recognition verification processing on the second depth image information.
The vehicle start control module 700 is configured to control whether the vehicle is started according to the result of the face recognition verification process.
The various modules in the keyless entry and start device of the vehicle of the present invention may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in the processor in the automobile control system in a hardware form or can be independent of the processor in the automobile control system, and can also be stored in the memory of the automobile control system in a software form, so that the processor can call and execute the operations corresponding to the modules.
The invention also provides a storage medium for realizing the keyless entry and starting method of the vehicle, wherein a program is stored on the storage medium, and the program realizes the following steps when being executed by a processor:
step S10, acquiring first depth image information of a person approaching a vehicle door, and performing face detection processing on the first depth image information;
step S20, performing living body detection processing on the first depth image information according to a face detection processing result, and performing identity verification processing on the first depth image information according to the living body detection processing result;
step S30, whether the vehicle door is unlocked or not is controlled according to the identity verification processing result;
step S40, after the vehicle door is unlocked, second depth image information of a driver of the vehicle is obtained, and face recognition verification processing is carried out on the second depth image information;
and step S50, controlling whether the vehicle is started or not according to the face recognition verification processing result.
Those skilled in the art will appreciate that all or part of the processes implementing the methods of the above embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a non-volatile computer readable storage medium, and the program may include processes of the embodiments of the methods described above when executed. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. A method for keyless entry and start-up of a vehicle, comprising:
acquiring first depth image information of a person approaching a vehicle door, and performing face detection processing on the first depth image information;
performing living body detection processing on the first depth image information according to a face detection processing result, and performing identity verification processing on the first depth image information according to the living body detection processing result;
controlling whether the vehicle door is unlocked or not according to the authentication processing result;
after the vehicle door is unlocked, second depth image information of a driver of the vehicle is obtained, and face recognition verification processing is carried out on the second depth image information; and
and controlling whether the vehicle is started or not according to the face recognition verification processing result.
2. The vehicle keyless entry and start method of claim 1, wherein the acquiring first depth image information of a person approaching a vehicle door comprises:
when the vehicle is in a parking and door locking state, acquiring depth image information outside the vehicle door at a standby acquisition frame rate through a first TOF camera installed at the vehicle door;
detecting the acquired depth image information to judge whether a person approaches the vehicle door; and
if the person is detected to be close to the car door, the first TOF camera is used for carrying out image acquisition processing on the person close to the car door at a work acquisition frame rate so as to acquire first depth image information of the person close to the car door, wherein the first depth image information comprises a depth image and a near infrared image.
3. The vehicle keyless entry and start method of claim 2, wherein the first depth image information includes a depth image and a near infrared image.
4. The keyless entry and start method of a vehicle according to claim 2, wherein said performing face detection processing on said first depth image information includes:
acquiring a near infrared image in the first depth image information, and sending the near infrared image into a face detection module for face detection; and
judging whether a human face exists in the near infrared image according to a human face detection processing result, if the human face is detected, performing living body detection processing and identity verification processing, if the human face is not detected, continuing to perform image acquisition on a person approaching a vehicle door through the first TOF camera at a work acquisition frame rate and performing human face detection processing again, and if the person is detected to leave, adjusting the acquisition frame rate of the first TOF camera to be a standby acquisition frame rate.
5. The vehicle keyless entry and start-up method according to any one of claims 1 to 4, characterized in that the performing a living body detection process on the first depth image information according to a face detection process result includes:
if the face detection processing result is that the face is detected, respectively performing image adjustment processing on the depth image and the near infrared image in the first depth image information;
carrying out gradient image processing on the depth image subjected to image adjustment processing to obtain gradient images in the horizontal direction, the vertical direction and the center-to-edge direction of the depth image, and combining the three gradient images into a three-channel depth image;
combining the depth image subjected to image adjustment processing with the near infrared image to obtain a three-channel gray level image;
sending the three-channel depth image into a living body detection model based on the depth image to calculate a depth image model score;
if the depth image model score is higher than a first living body threshold value, the three-channel gray level image is sent into a living body detection model based on a near infrared image to calculate a gray level image model score;
if the gray image model score is higher than a second living body threshold value, the three-channel depth image and the three-channel gray image are correspondingly placed into a depth image cache queue and a gray image cache queue;
repeatedly calculating model scores until the queue lengths of the depth image cache queue and the gray image cache queue are equal to preset values, respectively taking out three-channel depth images and three-channel gray images from the depth image cache queue and the gray image cache queue, and respectively emptying the depth image cache queue and the gray image cache queue;
respectively calculating LBP-TOP characteristics of the three-channel depth image and the three-channel gray image, splicing the LBP-TOP characteristics of the three-channel depth image and the three-channel gray image, and then putting the three-channel depth image and the three-channel gray image into a time sequence living body detection model based on comprehensive characteristics to calculate a time sequence model score; and
and if the time sequence model score is larger than a third living body threshold value, the time sequence model score is determined to be living body.
6. The keyless entry and start method of a vehicle according to claim 5, wherein the performing image adjustment processing on the depth image and the near-infrared image in the first depth image information, respectively, includes:
respectively carrying out orthodontic adjustment treatment on the depth image and the near infrared image;
respectively carrying out filtering treatment on the depth image and the near infrared image which are subjected to orthodontic adjustment treatment;
respectively carrying out dynamic compression processing on the depth image and the near infrared image which are subjected to filtering processing; and
and respectively carrying out gray value normalization processing on the depth image and the near infrared image which are subjected to dynamic compression processing.
7. The keyless entry and startup method of a vehicle according to claim 5, wherein the performing authentication processing on the first depth image information according to the living body detection processing result includes:
if the living body detection processing result is determined to be a living body, acquiring a near infrared image in the first depth image information; and
and comparing the near infrared image with an identity library of the local authorized unlocking vehicle, and unlocking the vehicle door if the comparison is passed.
8. The keyless entry and start method of a vehicle according to claim 1, wherein the acquiring second depth image information of a driver of the vehicle and performing face recognition verification processing on the second depth image information includes:
when the vehicle door is unlocked, acquiring depth image information outside the vehicle driving position at a standby acquisition frame rate through a second TOF camera installed at the vehicle driving position;
detecting the acquired depth image information to judge whether a person sits on a driver seat of the vehicle;
if the person is detected to be sitting on the vehicle driver seat, the second TOF camera is used for carrying out image acquisition processing on the vehicle driver seat person at a work acquisition frame rate so as to acquire second depth image information of the vehicle driver seat person;
sending the near infrared image in the second depth image information to a face detection module for face detection; and
judging whether a human face exists or not according to the human face detection processing result, if the human face is detected, comparing the near infrared image with an identity library of a local authorized starting vehicle, and if the comparison is passed, authorizing starting of the vehicle.
9. A keyless entry and start device for a vehicle, comprising:
a first TOF camera mounted at the door for acquiring first depth image information of a person approaching the door;
the second TOF camera is arranged at the vehicle driving position and is used for acquiring second depth image information of a person of the vehicle driving position;
the first depth image information processing module is used for acquiring first depth image information of a person approaching the vehicle door and carrying out face detection processing on the first depth image information;
the living body detection and identity verification module is used for carrying out living body detection processing on the first depth image information according to a human face detection processing result and carrying out identity verification processing on the first depth image information according to the living body detection processing result;
the door lock control module is used for controlling whether the door is unlocked or not according to the authentication processing result;
the second depth image information processing module is used for acquiring second depth image information of a vehicle driver after the vehicle door is unlocked and performing face recognition verification processing on the second depth image information; and
and the vehicle starting control module is used for controlling whether the vehicle is started or not according to the face recognition verification processing result.
10. A storage medium having a program stored thereon, wherein the program when executed by a processor performs the steps of the vehicle keyless entry and start method according to any one of claims 1 to 8.
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