CN108725357B - Parameter control method and system based on face recognition and cloud server - Google Patents
Parameter control method and system based on face recognition and cloud server Download PDFInfo
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- CN108725357B CN108725357B CN201810464343.1A CN201810464343A CN108725357B CN 108725357 B CN108725357 B CN 108725357B CN 201810464343 A CN201810464343 A CN 201810464343A CN 108725357 B CN108725357 B CN 108725357B
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Abstract
After the face features in the biological features of passengers are obtained, comparing the obtained face features with a preset face feature model, judging whether a face feature model matched with the face features exists in the preset face feature model or not, if the matched face feature model does not exist, obtaining and storing the face feature model according to the face features, and then storing the individual setting parameters of the vehicle corresponding to the face feature model; and if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters. Through the mode, the driving individuation setting of the passenger can be realized based on the face recognition technology, and the riding experience of the passenger is optimized.
Description
Technical Field
The application relates to the technical field of vehicle networking, in particular to a parameter control method and system based on face recognition and a cloud server.
Background
With the development of society and the improvement of living standard of people, automobiles become more and more important transportation tools for people to go out. The existing shared automobile technology is better and better developed, and people begin to select a shared automobile as a travel tool of the people.
However, each time the shared automobile is taken, the shared automobile needs to be set up by oneself, for example, the position of the seat is adjusted, the position of the rearview mirror is adjusted, and even the shared automobile is listened to by oneself through radio or music. These operations, along with their wasted time and effort, are detrimental to the driving and riding experience of the passengers. Or when driving a car in a school, due to the difference of objective factors such as the height, the body type and the habit of each person, a lot of time is spent on adjusting the configuration of the car such as a seat, a rearview mirror and the like every time, and the time of a student is greatly wasted. In addition, the other situation can be that a plurality of families only have one vehicle, the vehicle is often taken by a plurality of common passengers, when different passengers take the vehicle, parameters such as the height of a seat, the angle of a rearview mirror, the temperature of an air conditioner, the size of an air opening and the like need to be adjusted again, the operation is complex, and the passenger experience is poor.
Therefore, it is necessary to provide a parameter control method capable of automatically identifying different passengers, thereby realizing the driving individualization of the passengers.
Disclosure of Invention
An object of the present application is to provide a parameter control method and system based on face recognition and a cloud server, which can solve the above technical problems, and can realize personalized driving settings of vehicle passengers based on face recognition, thereby optimizing passenger experience.
In order to solve the technical problem, the application provides a parameter control method based on face recognition, which is applied to a vehicle and/or a cloud server, and the method comprises the following steps: acquiring biological characteristics of passengers, wherein the biological characteristics of the passengers comprise human face characteristics; comparing the human face features with a preset human face feature model, and judging whether a human face feature model matched with the human face features exists in the preset human face feature model or not; if the matched human face feature model does not exist, acquiring and storing the human face feature model according to the human face features; storing individual setting parameters of the vehicle corresponding to the face feature model; and if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters.
In one embodiment, the step of obtaining the biometric characteristic of the passenger comprises: acquiring a face picture of a passenger; converting the face picture into a gray image, and intercepting a face part in the gray image; and acquiring the human face characteristics according to the human face part.
In one embodiment, the personality setting parameters include working parameters of the vehicle and vehicle-mounted device use data, the working parameters of the vehicle-mounted device include at least one of seat parameters, rearview mirror parameters, air conditioner parameters and air outlet parameters, and the vehicle-mounted device use data include at least one of a display interface, a music list, a radio list, a history record, preference data, an intelligent reminder and account information.
In one embodiment, the step of acquiring and storing a face feature model according to the face features comprises: sequentially collecting face data of each angle to generate multi-dimensional face features; and generating a face feature model according to the multi-dimensional face features and storing the face feature model.
In one embodiment, the method further comprises: acquiring a modification operation instruction about the individual setting parameters; and updating the preset individual setting parameters corresponding to the face feature model according to the modification operation instruction.
In an embodiment, the step of updating the preset personality setting parameter corresponding to the face feature model according to the modification operation instruction includes: classifying and storing the modification operation instruction according to the time for acquiring the modification operation instruction; if the modification operation instructions are acquired for multiple times in the same time interval, updating preset personality setting parameters corresponding to the face feature model according to the last modification operation instruction; and if the modification operation instructions are acquired once in different time intervals, updating the preset individual setting parameters corresponding to the face feature model in the corresponding time interval according to the acquired modification operation instructions.
In one embodiment, the step of setting the preset personality setting parameter includes setting an operating parameter of a general mode and an operating parameter of a comfort mode, so that the personality setting parameter of the vehicle is automatically set to the preset personality setting parameter includes: if the working time of the vehicle-mounted device exceeds the preset time, setting the individual setting parameters of the vehicle-mounted device as the working parameters of the preset comfort mode; and if the working time of the vehicle-mounted device does not exceed the preset time, the individual setting parameter of the vehicle-mounted device is the working parameter of the preset common mode.
In one embodiment, the method further comprises: judging whether passengers are on the front passenger seat and the rear seat; if no passenger is on the front passenger seat and a passenger is on the back seat, the front-back distance of the front passenger seat is automatically adjusted to the forefront; if the passenger is on the front passenger seat and the passenger is not on the back seat, the front-back distance of the front passenger seat is automatically adjusted to the rearmost position.
The application also provides a parameter control system based on face recognition, and the system comprises a vehicle and a cloud server; the vehicle is used for acquiring the biological characteristics of the passenger, and the biological characteristics of the passenger comprise human face characteristics; the cloud server is used for comparing the face features with a preset face feature model and judging whether a face feature model matched with the face features exists in the preset face feature model or not; if the matched human face feature model does not exist, acquiring and storing the human face feature model according to the human face features; storing individual setting parameters of the vehicle corresponding to the face feature model; and if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature module so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters.
The application also provides a cloud server, which comprises a memory and a processor, wherein the memory stores at least one program instruction, and the processor loads and executes the at least one program instruction to realize the parameter control method based on the face recognition.
According to the parameter control method, the parameter control system and the cloud server based on the face recognition, after the face features in the biological features of passengers are obtained, the obtained face features are compared with a preset face feature model, whether a face feature model matched with the face features exists in the preset face feature model or not is judged, if the matched face feature model does not exist, the face feature model is obtained and stored according to the face features, and then the individual setting parameters of the vehicle corresponding to the face feature model are stored; and if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters. Through the mode, the driving individuation setting of the passenger can be realized based on the face recognition technology, and the riding experience of the passenger is optimized.
The foregoing description is only an overview of the technical solutions of the present application, and in order to make the technical means of the present application more clearly understood, the present application may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present application more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
Fig. 1 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment.
Fig. 2 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment.
Fig. 3 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment.
Fig. 4 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment.
Fig. 5 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment.
Fig. 6 is a schematic structural diagram illustrating a cloud server according to an exemplary embodiment.
Detailed Description
To further illustrate the technical means and effects of the present application for achieving the intended application purpose, the following detailed description is provided with reference to the accompanying drawings and preferred embodiments for specific embodiments, methods, steps, structures, features and effects thereof, which are provided by the parameter control method based on face recognition and the cloud server according to the present application.
The foregoing and other technical matters, features and effects of the present application will be apparent from the following detailed description of preferred embodiments, which is to be read in connection with the accompanying drawings. While the present application is susceptible to embodiment and specific details, specific reference will now be made in detail to the present disclosure for the purpose of illustrating the general principles of the invention.
The method provided by the application can be suitable for a cloud server or a vehicle. In the case of the same vehicle, the method can be applied to the vehicle-mounted terminal. The method can also be applied to a cloud server, and the cloud server executes the method when the passengers use different vehicles, for example, the method is applied to the cloud server when people use a shared vehicle. Of course, the method can also be applied to the cloud server and the vehicle, and parameter control based on face recognition is achieved through interaction between the cloud server and the vehicle.
Fig. 1 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment. Referring to fig. 1, the parameter control method based on face recognition of the present embodiment includes:
And step 110, acquiring the biological characteristics of the passenger, wherein the biological characteristics of the passenger comprise human face characteristics.
When a passenger opens the vehicle door to get on the vehicle, the opening signal of the vehicle door or the sensing signal of the seat triggers the biological characteristic acquisition device to acquire biological characteristics such as the vehicle-mounted camera, and at the moment, the vehicle-mounted camera starts to acquire the biological characteristics of the passenger and sends the biological characteristics to the cloud server and/or the vehicle for comparison. The biometric characteristic of the passenger can be the biometric characteristic of the passenger driving the vehicle, namely the driver, and can also be the biometric characteristic of other passengers on the vehicle. The biological features comprise human face features, and can also be a series of features which can be used for biological recognition, such as voiceprint features or pupil features. In addition, in the acquisition mode, the vehicle-mounted camera or other biological characteristic acquisition equipment can be triggered by a button on the vehicle and a specific gesture to acquire the facial characteristics in the biological characteristics, and when the vehicle-mounted camera is triggered to acquire the facial characteristics in the form of buttons, gestures and sentences with specific contents, a passenger can select whether the passenger carries out personalized setting or not according to actual needs, that is, the passenger can select whether the button is triggered, the gesture or the sentences with specific contents are spoken according to the actual needs, so that whether the vehicle carries out automatic personalized setting or not is controlled.
In one embodiment, step 110: the step of obtaining the biometric characteristic of the passenger comprises: acquiring a face picture of a passenger; converting the face picture into a gray image, and intercepting a face part in the gray image; and acquiring the human face characteristics according to the human face part.
The method comprises the steps of collecting the faces of passengers in a vehicle through a camera or a camera in the vehicle, converting the face pictures into gray images through the existing image processing technology, capturing face parts from the gray images, and finally storing the captured face parts as face features. At this time, the collected face picture can be collected at a certain angle or at multiple angles.
And step 120, comparing the face features with a preset face feature model, and judging whether a face feature model matched with the face features exists in the preset face feature model.
The human face features relate to a human face recognition technology. Face recognition is a biometric technology for identity recognition based on facial feature information of a person. The method includes acquiring an image or video stream containing a human face by using a camera or a video camera, automatically detecting and tracking the human face in the image, and further performing face comparison on the detected human face. In this embodiment, the obtained face features are compared with a preset face feature model, which is an authentication identification process. Specifically, the preset human face feature model is stored by the passenger in advance, and the human face features can be acquired from multiple angles through cameras in all directions in the vehicle, so that the human face feature model is established.
In one embodiment, step 120: the step of comparing the face features with a preset face feature model comprises the following steps: establishing a face feature model according to the received face features; and comparing the human face feature model with a preset human face feature model.
And step 130, if the matched human face feature model does not exist, acquiring and storing the human face feature model according to the human face features.
If the matched face features do not exist, it is indicated that the passenger does not drive the vehicle or has not collected the face features, and at this time, the face features may be obtained again or a face feature model of the passenger may be established directly according to the obtained face features.
In one embodiment, in step 110, the biometric features of the passenger are already obtained, and the face features in the obtained biometric features may be face features shot at a certain angle or face features shot at multiple angles. In order to realize the setting of the storage space and the quick response of the face recognition, the acquired face features are face features shot at a certain angle in general. Therefore, in order to establish the face feature model, the face features at other angles need to be acquired, that is, the face features need to be acquired again.
In one embodiment, step 130: the steps of acquiring and storing the face feature model according to the face features comprise: sequentially collecting face data of each angle to generate multi-dimensional face features; and generating a face feature model according to the multi-dimensional face features and storing the face feature model.
And step 140, storing the individual setting parameters of the vehicle corresponding to the face feature model.
Specifically, the personality setting parameters include operating parameters of the vehicle-mounted device and vehicle-mounted device usage data. The working parameters of the vehicle-mounted device comprise at least one of seat parameters, rearview mirror parameters, air conditioner parameters and air outlet parameters. The car machine is a vehicle-mounted information entertainment product installed in a car for short, CAN be used for realizing information communication between a person and a car and between the car and the outside (between the car and the car), the existing car machine develops from early CD and DVD navigation to intellectualization and informatization, and CAN have 3G and Telematics (vehicle-mounted information service) functions besides the basic functions of radio, music video playing and navigation, and CAN be combined with the CAN-BUS technology of the car to realize the information communication between the person and the car and between the car and the outside, so that passengers CAN remotely control the car through the internet, and even directly finish financial functions of shopping, payment and the like through the car. The vehicle-mounted device use data comprises at least one of a display interface, a music list, a radio station list, a historical record, preference data, an intelligent reminder and account information, is specifically determined according to the type of a passenger, is mainly personalized data for a driver, and can not be limited according to different setting modes of a vehicle-mounted device display screen and a vehicle-mounted device associated display screen in a vehicle during actual implementation.
And 150, if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to automatically set the personality setting parameters of the vehicle as the preset personality setting parameters.
In the process of carrying out authentication and identification on the face features, if the matched face feature model exists, the preset personality setting parameters corresponding to the face feature model are directly obtained, and then the personality setting parameters of the vehicle are automatically set to the preset personality setting parameters through the controller.
The individual setting parameters of the vehicle are, for example, a driving seat, an air conditioner, a rearview mirror, a driving seat air outlet, a vehicle-mounted display screen and the like. The vehicle-mounted networking service of multiple persons and multiple faces is provided for different passengers according to vehicle-mounted machine use data in the personality setting parameters, for example, radio station recommendation, music recommendation and path recommendation are carried out according to preference data corresponding to the current passenger, consumption payment is carried out according to account information of the current passenger in the personality setting parameters, related prompts are carried out according to an intelligent reminding mode corresponding to the current passenger in the personality setting parameters, and the like, so that the vehicle-mounted networking service can be adjusted according to changes of the current passenger, and is more intelligent and humanized.
The cloud server and/or the vehicle can be pre-stored with one or more face feature models, different passenger identities are distinguished according to the face feature models, and further the identity identifications of different passengers are corresponding to the face feature models. When the human face is identified, each acquired human face feature is compared and matched with each human face model stored in advance, and the similarity between each human face feature and each human face feature model is calculated, for example, when the human face features are acquired, each human face feature is compared with each human face feature model, the similarity between each human face feature and each human face model is calculated respectively, when the similarity between one human face feature and one human face model is greater than or equal to a set threshold value, the current passenger is the passenger corresponding to the human face feature model, and the identity of the passenger is determined.
Since the data acquisition is carried out on the individual setting parameters of the passengers before, at the moment, after the identification of the passenger is confirmed by authentication identification, the individual setting parameters of the vehicle are directly and automatically set as the preset individual setting parameters. For example, the vehicle-mounted device and the vehicle-mounted device are arranged in a series of three-dimensional arrangement of front and back, left and right and/or height of a seat, rear-view mirror angle, air-conditioning temperature and the like.
According to the parameter control method based on the face recognition, after the face features in the biological features of passengers are obtained, the obtained face features are compared with a preset face feature model, whether the face feature model matched with the face features exists in the preset face feature model or not is judged, if the matched face feature model does not exist, the face feature model is obtained and stored according to the face features, and then the individual setting parameters of the vehicle corresponding to the face feature model are stored; and if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters. Through the mode, the driving individuation setting of the passenger can be realized based on the face recognition technology, and the driving experience of the passenger is optimized.
Fig. 2 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment. On the basis of the foregoing embodiment, the parameter control method based on face recognition according to this embodiment further includes:
When the vehicle is not started or in the driving process, if the preset individual setting parameters cannot meet the requirements of the passengers, the passengers can adjust the individual setting parameters. For example, when a passenger needs to adjust a seat at a certain time, an input module, such as a touch screen or a microphone, inputs a modification operation instruction, that is, the vehicle can obtain the modification operation instruction through the input module, and the cloud server can receive the modification operation instruction through the communication module of the vehicle.
And step 220, updating preset personality setting parameters corresponding to the human face feature model according to the modification operation instruction.
Specifically, when the passenger takes the vehicle at this time, the vehicle can track changes of corresponding personality setting parameters in real time, such as adjustment of seat height, backrest angle, air conditioner temperature, air outlet size, air outlet direction, addition of favorite music, radio stations or increase of collected interest points, and the like, and the updated personality setting parameters can be uploaded to the cloud server, so that the passenger can automatically set the personality setting when taking the vehicle at the next time, and the user operation is simple and convenient.
In the parameter control method based on face recognition in the embodiment, on the basis of the embodiment, an operation instruction for modifying the personality setting parameters is further obtained, and the personality setting parameters are stored in real time when the passenger modifies the personality setting parameters. And then updating the preset individual setting parameters corresponding to the face feature model according to the result of the modification operation instruction. Through the embodiment, the adjustment parameters of the passenger on the individual setting parameters can be recorded in time, and the setting can be automatically updated when the passenger uses the vehicle next time. The passenger setting to the vehicle is greatly facilitated, and the riding experience of the passenger is improved.
Fig. 3 is a flowchart illustrating a parameter control method based on face recognition according to the above exemplary embodiment. On the basis of the foregoing embodiment, the updating of the preset personality setting parameter corresponding to the face feature model according to the modification operation instruction in the parameter control method based on face recognition according to the embodiment includes:
and 310, classifying and storing the modification operation instruction according to the time for acquiring the modification operation instruction.
The modification operation instructions are classified according to time intervals according to the time for obtaining the modification operation instructions, for example, the time intervals may be classified for one interval according to 8 hours or other time periods, and such classification manners may be set according to different habits of passengers in driving vehicles at different times. Specifically, when the classification is performed for a time interval of 8 hours, the modification operation command may be classified into three classes, i.e., 0 to 8 points, 8 to 16 points, and 16 to 24 points, according to the acquired time.
And 320, if the modification operation instructions are acquired for multiple times in the same time interval, updating the preset personality setting parameters corresponding to the face feature model in the corresponding time interval according to the acquired modification operation instructions.
The passenger modification operation instructions are classified according to the time interval, and when the passenger adjusts the personality setting parameters in the same time interval, for example, the modification operation instructions are divided according to morning and evening, if the passenger adjusts the personality setting parameters in the morning for the first time, the preset personality setting parameters in the morning are stored as the personality setting parameters after the passenger adjusts for the first time. If the passenger adjusts the personality setting parameters in the morning for the second time, the preset personality setting parameters in the morning are directly updated to the personality setting parameters after the second adjustment.
And 330, if the modification operation instructions are acquired once in different time intervals, updating preset personality setting parameters corresponding to the face feature model in the corresponding time interval according to the acquired modification operation instructions.
Based on the example in step 320, when the passenger adjusts the personality setting parameters in the morning and in the evening, the preset personality setting parameters in the morning are updated to the personality setting parameters adjusted by the passenger in the morning, and the preset personality setting parameters in the evening are updated to the personality setting parameters adjusted by the passenger in the evening.
The parameter control method based on face recognition shown in the embodiment is based on the above embodiment, and further classifies and stores the modification operation instruction according to the time of the modification operation instruction, and if the modification operation instruction is obtained for multiple times in the same time interval, updates the preset personality setting parameter corresponding to the face feature model according to the last modification operation instruction; and if the modification operation instructions are acquired once in different time intervals, updating the preset individual setting parameters corresponding to the face feature model in the corresponding time interval according to the acquired modification operation instructions. Through the embodiment, the adjustment parameters of the passengers to the individual setting parameters can be recorded according to time classification, and the setting can be automatically updated when the passengers use the vehicle next time. The passenger can set the vehicle conveniently, and the riding experience of the passenger is improved.
Fig. 4 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment. On the basis of the foregoing embodiment, in the parameter control method based on face recognition of this embodiment, the preset personality setting parameters include working parameters of a preset common mode and working parameters of a preset comfort mode, so that the step of automatically setting the personality setting parameters of the vehicle to the preset personality setting parameters includes:
And step 410, if the working time of the vehicle-mounted device exceeds the preset time, setting the individual setting parameter of the vehicle-mounted device as the working parameter of the preset comfort mode.
When the working time of the vehicle-mounted device exceeds the preset time, for example, the passenger drives the vehicle for more than 3 hours. The preset time is 2 hours by default, but is not limited to 2 hours, and may be preset according to the situation of the passenger. At this time, the individual setting parameters of the vehicle are set as the working parameters of the preset comfort mode, and the working parameters of the comfort mode can be obtained by combining the big data analysis according to the habits of the user or can be set in advance by the user according to the habits of the user. The cpu then sends the operating parameters to each controller, for example, the controller that controls the vehicle-mounted devices such as the windows, the seat, and the backrest.
In step 420, if the working time of the vehicle-mounted device does not exceed the preset time, the personal setting parameter of the vehicle-mounted device is the working parameter of the preset common mode.
In the parameter control method based on face recognition, based on the above embodiments, the working time of the vehicle-mounted device is determined, and if the working time of the vehicle-mounted device exceeds the preset time, the individual setting parameters are set as the working parameters of the preset comfort mode, and the working parameters are sent to each controller through the processor, and the controllers adjust the relevant individual setting parameters according to the working parameters. And when the working time of the vehicle-mounted device does not exceed the preset time, the individual setting parameter of the vehicle-mounted device is the working parameter of the preset common mode. Through this embodiment, the operating time to the mobile unit has been judged, has greatly made things convenient for the passenger to the setting of vehicle, promotes the long-distance experience of driving of passenger.
Fig. 5 is a flowchart illustrating a parameter control method based on face recognition according to an exemplary embodiment. On the basis of the foregoing embodiment, the parameter control method based on face recognition according to this embodiment further includes:
and step 510, judging whether passengers are on the front passenger seat and the rear seat.
And 520, if no passenger is in the front passenger seat and a passenger is in the back seat, automatically adjusting the front-back distance of the front passenger seat to the forefront.
And step 530, if the passenger is in the front passenger seat and the passenger is not in the back seat, automatically adjusting the front-back distance of the front passenger seat to the rearmost position.
In the parameter control method based on face recognition according to the present embodiment, it is determined whether or not a passenger is present in the front passenger seat and the rear seat on the basis of the above embodiment; and when no passenger is on the front passenger seat and a passenger is on the back seat, the front-back distance of the front passenger is automatically adjusted to the forefront. And if the passenger is in the front passenger seat and the passenger is not in the rear seat, the front-rear distance of the front passenger seat is automatically adjusted to the rearmost position. According to the embodiment, under the condition that no passenger is on the passenger seat, the passenger seat is moved forwards, and the riding experience of the passengers on the rear row of the automobile can be improved. When the passenger is on the front passenger seat and the passenger is not on the back seat, the front-back distance of the front passenger seat is automatically adjusted to the rearmost position, the activity space of the front passenger seat is enlarged, and the riding experience of the passenger is improved.
Simultaneously, this application still provides a vehicle control system based on face identification, and this system includes vehicle and high in the clouds server.
The vehicle is used for acquiring the biological characteristics of the passenger, and the biological characteristics of the passenger comprise human face characteristics; the cloud server is used for comparing the face features with a preset face feature model and judging whether a face feature model matched with the face features exists in the preset face feature model or not; if the matched human face feature model does not exist, acquiring and storing the human face feature model according to the human face features; storing individual setting parameters of the vehicle corresponding to the face feature model; and if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature module so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters.
Through the system that this embodiment provided, can conveniently use the setting of sharing car or the passenger who possess many cars alone to the car, promote passenger's the experience of driving and taking a bus.
Fig. 6 is a schematic structural diagram illustrating a cloud server according to an exemplary embodiment. The application further provides a cloud server, which includes a memory 610 and a processor 620, where the memory 610 stores at least one program instruction, and the processor 620 implements the method shown in fig. 1 by loading and executing the at least one program instruction:
Step 110: acquiring biological characteristics of passengers, wherein the biological characteristics of the passengers comprise human face characteristics;
step 120: comparing the human face features with a preset human face feature model, and judging whether a human face feature model matched with the human face features exists in the preset human face feature model or not;
step 130: if the matched human face feature model does not exist, acquiring and storing the human face feature model according to the human face features;
step 140: storing individual setting parameters of the vehicle corresponding to the face feature model;
step 150: and if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters.
According to the cloud server, after the face features in the biological features of the passengers are obtained, the obtained face features are compared with a preset face feature model, whether the face feature model matched with the face features exists in the preset face feature model or not is judged, if the matched face feature model does not exist, the face feature model is obtained and stored according to the face features, and then the individual setting parameters of the vehicle corresponding to the face feature model are stored; and if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters. Through the mode, the driving individuation setting of the passenger can be realized based on the face recognition technology, and passenger experience is optimized.
For details of the step process of the processor 620 in the cloud server of this embodiment calling the executable program code in the memory 610, please refer to details described in the embodiment shown in fig. 1, which are not described herein again.
Although the present application has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the application, and all changes, substitutions and alterations that fall within the spirit and scope of the application are to be understood as being included within the following description of the preferred embodiment.
Claims (7)
1. A parameter control method based on face recognition is applied to a vehicle and/or a cloud server, and comprises the following steps:
acquiring biological characteristics of passengers, wherein the biological characteristics of the passengers comprise human face characteristics;
Comparing the human face features with a preset human face feature model, and judging whether a human face feature model matched with the human face features exists in the preset human face feature model or not;
if the matched human face feature model does not exist, acquiring and storing a human face feature model according to the human face features;
storing individual setting parameters of the vehicle corresponding to the face feature model;
if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to automatically set the personality setting parameters of the vehicle to the preset personality setting parameters;
wherein, the preset personal setting parameters comprise working parameters of a preset common mode and working parameters of a preset comfort mode, and the step of automatically setting the personal setting parameters of the vehicle to the preset personal setting parameters comprises the following steps:
if the working time of the vehicle-mounted device exceeds the preset time, setting the individual setting parameter of the vehicle-mounted device as the working parameter of a preset comfort mode;
if the working time of the vehicle-mounted device does not exceed the preset time, setting the individual setting parameter of the vehicle-mounted device as the working parameter of a preset common mode;
Wherein the method further comprises:
acquiring a modification operation instruction about the individual setting parameters;
updating preset individual setting parameters corresponding to the face feature model according to the modification operation instruction;
the step of updating the preset individual setting parameters corresponding to the face feature model according to the modification operation instruction comprises the following steps:
classifying and storing the modification operation instruction according to the time for acquiring the modification operation instruction;
if the modification operation instructions are acquired for multiple times in the same time interval, updating the preset individual setting parameters according to the last modification operation instruction;
and if the modification operation instructions are acquired once in different time intervals, updating the preset individual setting parameters of the corresponding time intervals according to the acquired modification operation instructions.
2. The parameter control method based on face recognition according to claim 1, wherein the step of acquiring the biometric features of the passenger comprises:
acquiring a face picture of a passenger;
converting the face picture into a gray image, and intercepting a face part in the gray image;
and acquiring the human face characteristics according to the human face part.
3. The parameter control method based on the face recognition according to claim 1, wherein the personality setting parameters of the vehicle comprise working parameters of a vehicle-mounted device and vehicle-mounted device use data, the working parameters of the vehicle-mounted device comprise at least one of seat parameters, rearview mirror parameters, air-conditioning parameters and air outlet parameters, and the vehicle-mounted device use data comprise at least one of a display interface, a music list, a radio station list, a history record, preference data, an intelligent reminder and account information.
4. The parameter control method based on face recognition according to claim 1, wherein the step of obtaining and storing a face feature model according to the face features comprises:
sequentially collecting face data of each angle to generate multi-dimensional face features;
and generating a face feature model according to the multi-dimensional face features and storing the face feature model.
5. The parameter control method based on face recognition according to claim 1, wherein the method further comprises:
judging whether passengers are on the front passenger seat and the rear seat;
if no passenger is on the front passenger seat and a passenger is on the back seat, the front-back distance of the front passenger seat is automatically adjusted to the forefront;
If the passenger is on the front passenger seat and the passenger is not on the back seat, the front-back distance of the front passenger seat is automatically adjusted to the rearmost position.
6. A parameter control system based on face recognition is characterized by comprising a vehicle and a cloud server;
the vehicle is used for acquiring the biological characteristics of passengers, and the biological characteristics of the passengers comprise human face characteristics;
the cloud server is used for comparing the face features with a preset face feature model and judging whether a face feature model matched with the face features exists in the preset face feature model or not; if the matched human face feature model does not exist, acquiring and storing a human face feature model according to the human face features; storing individual setting parameters of the vehicle corresponding to the face feature model; if the matched human face feature model exists, acquiring preset personality setting parameters corresponding to the human face feature model so as to enable the personality setting parameters of the vehicle to be automatically set to the preset personality setting parameters, wherein the preset personality setting parameters comprise working parameters of a preset common mode and working parameters of a preset comfortable mode, and the automatic setting of the personality setting parameters of the vehicle to the preset personality setting parameters comprises the following steps: if the working time of the vehicle-mounted device exceeds the preset time, setting the individual setting parameter of the vehicle-mounted device as the working parameter of a preset comfort mode; if the working time of the vehicle-mounted device does not exceed the preset time, setting the individual setting parameters of the vehicle-mounted device as the working parameters of a preset common mode;
The cloud server is further configured to obtain a modification operation instruction about the personality setting parameter, and update a preset personality setting parameter corresponding to the face feature model according to the modification operation instruction, where updating the preset personality setting parameter corresponding to the face feature model according to the modification operation instruction includes: and classifying and storing the modification operation instruction according to the time of obtaining the modification operation instruction, if the modification operation instruction is obtained for multiple times in the same time interval, updating the preset individual setting parameters according to the last modification operation instruction, and if the modification operation instruction is obtained once in different time intervals, updating the preset individual setting parameters of the corresponding time interval according to the obtained modification operation instruction.
7. Cloud server, comprising a memory and a processor, wherein the memory stores at least one program instruction, and the processor implements the parameter control method based on face recognition according to any one of claims 1 to 5 by loading and executing the at least one program instruction.
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