CN115959013A

CN115959013A - Vehicle seat setting method, device and storage medium based on face recognition

Info

Publication number: CN115959013A
Application number: CN202211734331.9A
Authority: CN
Inventors: 颜专
Original assignee: Guangzhou Lango Electronic Science and Technology Co Ltd
Current assignee: Guangzhou Lango Electronic Science and Technology Co Ltd
Priority date: 2022-12-30
Filing date: 2022-12-30
Publication date: 2023-04-14

Abstract

The application provides a vehicle seat setting method, equipment and a storage medium based on face recognition, wherein the method comprises the following steps: the method comprises the following steps of S1, collecting face information and driving preference information of a user in advance, wherein the driving preference information comprises driving position setting information and vehicle setting information; s2, when the human face exists in the vehicle, acquiring a human face image of a user in the vehicle, and matching the human face image with human face information collected in advance to confirm identity information of the user; and S3, receiving an identity information confirmation instruction sent by a mobile terminal or a vehicle terminal bound by a vehicle, acquiring driving preference information according to the identity information of the user, and setting driving position setting information and/or vehicle setting information according to the driving preference information. The method and the device can quickly acquire the driver information, automatically set the corresponding vehicle driving preference and habit, and can be applied to various vehicle types.

Description

Vehicle seat setting method, device and storage medium based on face recognition

Technical Field

The application relates to the technical field of computers, in particular to a vehicle seat setting method, device and storage medium based on face recognition.

Background

For most families, domestic small vehicles are commonly used by both couples, and for differences in the bodies and characters of males and females, certain differences exist in the running modes of the vehicles, the use methods of devices in the vehicles and other aspects, and the current face recognition verification of the identity information of the drivers starts to be popularized, so that a set of complete personalized setting of driving in the vehicles can be correspondingly provided for the drivers.

However, face recognition on vehicles is not widely popularized yet, audiences are not wide enough, and for vehicles which do not provide face recognition, a set of face recognition and regulation and control equipment with functions in the vehicles may need to be independently installed, so that the cost is possibly too high. The driving service provided by each vehicle type, the internal control logic and the like are different, and the vehicle type-specific driving method can be developed only for specific vehicle types and cannot be applied to more vehicle types.

Disclosure of Invention

In order to solve the above problems, embodiments of the present application provide a method, an apparatus, and a storage medium for setting a vehicle seat based on face recognition, which are used to quickly obtain driver information and automatically set corresponding driving preferences and habits of a vehicle.

The application provides a vehicle seat setting method based on face recognition, which comprises the following steps:

the method comprises the following steps of S1, collecting face information and driving preference information of a user in advance, wherein the driving preference information comprises driving position setting information and vehicle setting information;

s2, when the human face exists in the vehicle, acquiring a human face image of a user in the vehicle, and matching the human face image with human face information collected in advance to confirm identity information of the user;

and S3, receiving an identity information confirmation instruction sent by a mobile terminal or a vehicle terminal bound by a vehicle, acquiring driving preference information according to the identity information of the user, and setting driving position setting information and/or vehicle setting information according to the driving preference information.

Optionally, with reference to any one of the foregoing aspects, in another implementation manner of this aspect, the method further includes the following steps:

s4, acquiring the driving state of the current vehicle and the face image of the driving position at preset time intervals, and extracting expression characteristic data in the face image; and judging whether the driving state is matched with the expression state data in the face image, and sending a seat adjustment prompt when the driving state is not matched with the expression state data in the face image.

Optionally, in combination with any one of the above aspects, in another implementation manner of the present aspect, the current driving state of the vehicle includes high speed driving, low speed driving, and stop driving; when the vehicle is in a high-speed driving state or a low-speed driving state within a preset time interval, extracting facial feature data in the real-time face image, and judging whether the facial feature data of the driver are matched with the data of the driving state or not according to the facial feature data; the facial feature data comprise facial expressions, the heights of eyes, lips and heads, and when the difference between the facial feature data and a preset standard value of the user exceeds a threshold value, the facial feature data are judged not to be matched with the current driving state, and a seat adjustment prompt is sent.

Optionally, with reference to any one of the foregoing aspects, in another implementation manner of the present aspect, the step S2 matches the face image with face information collected in advance, specifically, identifies and removes an occlusion part of the face image, and extracts feature information of the face image from which the occlusion part is removed; and matching the characteristic information of the face image without the shielding part with the face information collected in advance, and determining a threshold value for successful matching judgment according to the area size of the shielding part and the characteristic information.

Optionally, with reference to any one of the foregoing aspects, in another implementation manner of the present aspect, the step S2 further includes the following steps:

step S21, matching the face image with face information collected in advance, and acquiring environment information of the position where the user is located when the face image is unsuccessfully matched with the face information collected in advance;

and S22, calculating body type information of the user according to the environment information of the position of the user, and matching the corresponding vehicle setting information and/or driving position setting information by the body type information.

and S23, recording the face information, the body type information and the driving preference information of the user after receiving the user confirmation instruction.

Optionally, with reference to any one of the foregoing aspects, in another implementation manner of this aspect, the driving seat setting information includes driving seat position information, driving seat air conditioner temperature and air conditioner wind direction setting information, rear view mirror setting information, steering wheel height or comfort setting information, music mode and volume information; the vehicle setting information comprises setting information of the height and the position of a seat of a rear row or a copilot, setting information of the temperature and the wind direction of an air conditioner, and music mode and volume information.

Optionally, in combination with any one of the above aspects, in another implementation manner of the present aspect, the seat adjustment prompt includes an adjustment seat inquiry, a seat vibration, and a seat back adjustment.

In another aspect of the present application, an electronic device is provided, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the processor implements a method for setting a vehicle seat based on face recognition as described in any one of the above.

In another aspect of the present application, there is provided a storage medium having stored thereon a computer program which, when executed, implements a face recognition-based vehicle seat setting method as recited in any one of the above.

As described above, the present application provides a method, a device, and a storage medium for setting a vehicle seat based on face recognition, which pre-collect face information and driving preference information of a user, identify the face information when detecting that a face image exists in a vehicle, and then adjust driving seat setting information and vehicle setting information in the vehicle according to the identity information, thereby rapidly adjusting the driving seat or the seat in the vehicle or the environment setting in the vehicle. According to the method and the device, new regulation and control equipment is not required to be additionally arranged, the seat can be quickly adjusted only by acquiring the face information of the user, and the driving comfort of the user is improved.

The above summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. The above summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. The claimed subject matter is not limited to implementations that solve any or all disadvantages noted in the background.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and, together with the description, serve to explain the principles of the application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.

FIG. 1 is a schematic flow chart of a vehicle seat setting method based on face recognition according to the present application;

fig. 2 is a schematic flow chart of step S2 of a vehicle seat setting method based on face recognition according to the present application.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the application, as detailed in the appended claims.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element, and further, components, features, elements, and/or steps that may be similarly named in various embodiments of the application may or may not have the same meaning, unless otherwise specified by its interpretation in the embodiment or by context with further embodiments.

It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope herein. The word "if," as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination," depending on the context. Also, as used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, steps, operations, elements, components, species, and/or groups thereof. As used herein, the terms "or," "and/or," "including at least one of the following," and the like, are to be construed as inclusive or meaning any one or any combination. An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some way.

It should be understood that, although the steps in the flowcharts in the embodiments of the present application are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, in different orders, and may be performed alternately or at least partially with respect to other steps or sub-steps of other steps.

The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.

It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

Referring to fig. 1, the present application provides a vehicle seat setting method, apparatus, device, and storage medium based on face recognition, which quickly obtain driver information, automatically set corresponding vehicle driving preferences and habits, and improve driving experience.

Specifically, the method comprises the following steps:

the method comprises the following steps of S1, collecting face information and driving preference information of a user in advance, wherein the driving preference information comprises driving position setting information and vehicle setting information. The user can collect face information in advance through a face recognition camera positioned inside the vehicle or through a mobile terminal bound by the vehicle. In the process, the face information which is shot under the environment of light comparison without any shielding of the user needs to be collected. When the face information is collected, the corresponding driving preference information is collected.

The driving preference information includes driving seat setting information and vehicle setting information. The driving position setting information is information which needs to be set by a vehicle driver in the driving process, and comprises driving position seat position information, driving position air conditioner temperature and air conditioner wind direction setting information, rear-view mirror setting information, steering wheel height or comfort setting information, music mode and volume information. By collecting the above information, the driver can be helped to quickly adjust the interior of the vehicle to a suitable driving environment. The vehicle setting information is set by all passengers in the vehicle, including but not limited to a driver, a passenger seat, a rear passenger seat and the like, and includes seat height and position setting information of the rear passenger seat or the passenger seat, air conditioner temperature and air conditioner wind direction setting information, music mode and volume information. Through setting up vehicle setting information, be convenient for carry out subregion control to the vehicle, provide more comfortable environment of taking for the passenger.

And S2, when the human face exists in the vehicle, acquiring a human face image of a user in the vehicle, and matching the human face image with human face information collected in advance to confirm the identity information of the user.

The face recognition detection device is arranged in the vehicle, and a face image can be shot by a face recognition camera or a simple high-definition camera. The camera is generally arranged right ahead of the driving seat or the copilot, and can acquire a relatively comprehensive image in the vehicle. And the corresponding seat which is convenient for the back adjustment is obtained by matching with a pressure sensor on the seat to obtain the position of the seat where the face image is positioned.

In real life, drivers or passengers may wear masks, sunglasses, scarves and other articles for keeping warm, keeping healthy, assisting driving and the like. This may cause a phenomenon that matching is not successful or matching is wrong in the face recognition process. Therefore, in the application, the face image is matched with the face information collected in advance, specifically, the shielding part of the face image is identified and removed, and the characteristic information of the face image with the shielding part removed is extracted; and matching the characteristic information of the face image without the shielding part with the face information collected in advance, and determining a threshold value for successful matching judgment according to the area size of the shielding part and the characteristic information. In general, the larger the area of the shielding part is, the smaller the position of extracting the remaining feature extraction information in the face image is, so that the higher the threshold value should be set to improve the accuracy of the face recognition position.

When the passenger or driver is using the vehicle for the first time, this occurs as shown in fig. 2:

s21, matching the face image with face information collected in advance, and acquiring environment information of the position of a user when the face image is unsuccessfully matched with the face information collected in advance; the environment information includes a seat where the user is located and a seat position. The seat position refers to a position of the seat on the movement track, and can be obtained through a seat adjusting device in the vehicle, and generally, a user can perform simple adjustment after getting on the vehicle, so the seat position adjusted by the user is used as the standard in the process.

And S22, calculating body type information of the user according to the environment information of the position of the user, and matching the corresponding vehicle setting information and/or driving position setting information by the body type information. The method comprises the steps that the body type information of a user is preliminarily calculated according to the environment information of the position of the user, specifically the position of a seat and the height or the weight of the user estimated in a face image, so that the vehicle setting information and/or the driving position setting information can be estimated according to the height and the weight.

And S23, after receiving a user confirmation instruction, recording the face information, the body type information and the driving preference information of the user. After the setting of the environment in the seat or the vehicle is completed, if the driving preference information of the user needs to be recorded, the face information, the driving preference information and the like of the user can be recorded only by a user confirmation instruction sent by the vehicle-bound mobile terminal or the vehicle-bound user on the vehicle.

More, the method also comprises the following steps:

s4, acquiring the driving state of the current vehicle and the face image of the driving position at preset time intervals, and extracting face feature data in the face image; and judging whether the driving state is matched with the facial feature data in the face image, and sending a seat adjustment prompt when the driving state is not matched with the facial feature data in the face image.

The current driving state of the vehicle includes high-speed running, low-speed running, and stopped running. When the vehicle runs at a high speed or a low speed for a long time, a driver is easy to have fatigue, poor eyes, doze and the like, so that the vehicle is easy to be driven to have unsafe conditions. Therefore, when the vehicle is in a high-speed driving state or a low-speed driving state within a preset time interval, the facial feature data in the real-time human face image are extracted. Judge whether driver's facial feature data and driving state's data match through facial feature data, wherein facial feature data include facial expression, eyes, lip etc. the height of head carries out comprehensive judgement, if eyes are squinting or semi-conjunctive, when the height of head is in the height of driving unnormally or differs the head height that carries out face identification before with and exceeds the threshold value, then judge that this facial feature data does not match with current driving state, send the seat adjustment suggestion. The seat adjustment prompt comprises adjustment seat inquiry, seat vibration and seat backrest adjustment, and the driving attention of a driver is concentrated and the driving safety of a vehicle is improved through the seat adjustment prompt.

The invention provides a vehicle seat setting method based on face recognition, which collects face information and driving preference information of a user in advance, identifies identity information when a face image is detected in a vehicle, and adjusts driving position setting information and vehicle setting information in the vehicle according to the identity information, thereby quickly adjusting the driving position or the seat in the vehicle or the environment setting in the vehicle. According to the method and the device, new regulation and control equipment is not required to be additionally arranged, the seat can be quickly adjusted only by acquiring the face information of the user, and the driving comfort of the user is improved.

The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.

In the present application, the same or similar descriptions of terms, technical solutions and/or application scenarios will generally be described in detail only when they occur for the first time, and when they occur repeatedly later, they will not be repeated again for brevity, and in understanding the technical solutions and the like of the present application, reference may be made to the related detailed descriptions and the like before the same or similar descriptions of terms, technical solutions and/or application scenarios and the like which are not described in detail later.

In the present application, each embodiment is described with emphasis, and reference may be made to the description of other embodiments for parts that are not described or illustrated in any embodiment.

The technical features of the technical solution of the present application may be arbitrarily combined, and for brevity of description, all possible combinations of the technical features in the embodiments are not described, however, as long as there is no contradiction between the combinations of the technical features, the scope of the present application should be considered as being described in the present application.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) as above and includes several instructions for enabling a terminal device (which may be an electric device or a network device, etc.) to execute the method of each embodiment of the present application.

The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.

Claims

1. A vehicle seat setting method based on face recognition is characterized by comprising the following steps:

2. The face recognition-based vehicle seat setting method as claimed in claim 1, wherein: further comprising the steps of:

3. A vehicle seat setting method based on face recognition as set forth in claim 2, wherein: the current driving state of the vehicle comprises high-speed driving, low-speed driving and stopping driving; when the vehicle is in a high-speed driving state or a low-speed driving state within a preset time interval, extracting facial feature data in the real-time face image, and judging whether the facial feature data of the driver are matched with the data of the driving state or not according to the facial feature data; the facial feature data comprise facial expressions, the heights of eyes, lips and heads, and when the difference between the facial feature data and a preset standard value of the user exceeds a threshold value, the facial feature data are judged not to be matched with the current driving state, and a seat adjustment prompt is sent.

4. A vehicle seat setting method based on face recognition as claimed in claim 3, wherein: matching the face image with face information collected in advance in the step S2, specifically, identifying and removing the shielding part of the face image, and extracting the feature information of the face image with the shielding part removed; and matching the characteristic information of the face image without the shielding part with the face information collected in advance, and determining a threshold value for successful matching judgment according to the area size of the shielding part and the characteristic information.

5. The face recognition-based vehicle seat setting method as claimed in claim 4, wherein: the step S2 further includes the steps of:

s21, matching the face image with face information collected in advance, and acquiring environment information of the position of a user when the face image is unsuccessfully matched with the face information collected in advance;

and S22, calculating body type information of the user according to the environment information of the position of the user, and matching the corresponding vehicle setting information and/or driving position setting information according to the body type information.

6. The face recognition-based vehicle seat setting method as claimed in claim 5, wherein: further comprising the steps of:

7. A vehicle seat setting method based on face recognition as claimed in claim 2, wherein: the driving position setting information comprises driving position seat position information, driving position air conditioner temperature and air conditioner wind direction setting information, rearview mirror setting information, steering wheel height or comfort setting information, music mode and volume information; the vehicle setting information comprises the height and position setting information of a seat of a rear row or a copilot, the air conditioner temperature and air conditioner wind direction setting information, the music mode and the volume information.

8. A vehicle seat setting method based on face recognition as claimed in claim 3, wherein: the seat adjustment prompt includes an adjustment seat query, a seat vibration, and a seat back adjustment.

9. An electronic device, comprising a processor, a memory, and a computer program stored in the memory and operable on the processor, wherein the processor executes the computer program to implement a method for setting a vehicle seat based on face recognition according to any one of claims 1 to 8.

10. A storage medium having stored thereon a computer program which, when executed, implements a face recognition-based vehicle seat setting method according to any one of claims 1 to 8.