CN114619993A - Automobile control method based on face recognition, system, equipment and storage medium thereof - Google Patents
Automobile control method based on face recognition, system, equipment and storage medium thereof Download PDFInfo
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Abstract
The invention provides a face recognition-based automobile control method, which comprises the steps of obtaining a first face detection result and a first face recognition result through a first face detection recognition network, and determining an unlocking mode of an automobile according to the first face recognition result; after the automobile is successfully unlocked, obtaining a second face detection result, and performing comparison operation on the second face detection result and prestored face information to determine the identity of an automobile driver; and acquiring a second face detection result, performing comparison operation on the second face detection result and prestored face information to determine the identity of the automobile driver, and adjusting the corresponding driving part of the automobile according to the driving part adjusting information after determining that the identity of the automobile driver is a user. The invention improves the safety and convenience of automobile unlocking, and intelligently adjusts the driving parts of the automobile, thereby providing convenience for automobile users. The invention also provides a system, equipment and a storage medium for realizing the automobile control method based on face recognition.
Description
Technical Field
The invention relates to the field of automobile control, in particular to an automobile control method based on face recognition, a system, equipment and a storage medium thereof.
Background
With the continuous improvement of living conditions, private cars have become the main means of transportation for people to go out, and bring convenience to the lives of people. Meanwhile, traffic accidents, particularly drunk driving, also become the chief culprit of harming lives and properties. More and more drivers are aware of the harm of drunk driving, and the drunk driving is taken as an emerging industry in the background.
Although the designated driving brings convenience to the owner, the designated driving brings trouble at the same time. Because each driver has different driving habits, driving components such as a seat, a left mirror, a right mirror, a rear view mirror, the height of a steering wheel and the like are adjusted according to own habits before driving. After the modern driving service is finished, the driving part of the automobile can not return to the original state of the automobile, an automobile user needs to manually adjust the driving part again according to own habits, and the position of the driving part which is adjusted again is difficult to be adjusted to the optimal position which is adjusted last time by the user, so that troubles and puzzles are caused to the automobile user.
Chinese patent publication No. CN203637689U discloses an automobile rearview mirror surface steering gear and a memory assembly thereof, wherein the memory assembly comprises a memory unit bracket, a carbon film plate, a carbon film brush sheet and a potentiometer gear which are connected in sequence, and the joints of the memory unit bracket, the carbon film plate, the carbon film brush sheet and the potentiometer gear are coaxially arranged. The automobile rearview mirror surface steering gear is provided with the memory component. The utility model discloses a realize adjusting car owner's rear-view mirror through the memory subassembly to make the rear-view mirror resume the position and the angle that set up before the car owner. Since the component information stored in the memory unit is limited when the vehicle has a plurality of users, the position information of the driving components of all the users cannot be stored well. But the utility model discloses do not solve the problem that needs manual regulation driver part after the auto change driver.
Therefore, it is necessary to provide a car control method based on face recognition, a system, a device and a storage medium thereof to solve the above-mentioned problems in the prior art.
Disclosure of Invention
The invention aims to provide an automobile control method based on face recognition, a system, equipment and a storage medium thereof, which aim to solve the problem that the automobile needs to manually adjust driving parts each time a driver is replaced.
In order to achieve the above object, the automobile control method based on face recognition of the invention comprises the following steps:
s1: acquiring a first human face detection result through a first human face detection and identification network, performing comparison operation on the first human face detection result and prestored human face information to acquire a first human face identification result, and determining an unlocking mode of the automobile according to the first human face identification result;
s2: after the automobile is successfully unlocked in the automobile unlocking mode, a second face detection result is obtained through a second face detection and recognition network, and comparison operation is carried out on the second face detection result and the prestored face information to determine the identity of an automobile driver;
s3: and after the identity of the automobile driver is determined as the user, extracting the driving part adjusting information corresponding to the prestored face information matched with the user, and adjusting the driving part of the automobile according to the driving part adjusting information.
The automobile control method based on face recognition has the beneficial effects that:
a first face detection result is obtained through the first face detection and identification network, comparison operation is carried out on the first face detection result and the prestored face information to obtain a first face identification result, and an unlocking mode of the automobile is determined according to the first face identification result, so that the safety and the convenience of automobile unlocking are improved; after the automobile is successfully unlocked, a second face detection result is obtained through a second face detection and recognition network, and comparison operation is carried out on the second face detection result and the prestored face information to determine the identity of the driver; after the identity of the automobile driver is determined as a user, extracting driving part adjusting information corresponding to prestored face information matched with the user, and adjusting the driving part of the automobile according to the driving part adjusting information. The invention improves the safety and convenience of automobile unlocking by detecting the face information and determining the unlocking mode of the automobile, determines the driver identity of the automobile according to the comparison result of the face similarity and the similarity threshold, and determines the adjustment information of the driving part according to the internal face information matched with the user if the automobile driver is the user, thereby intelligently adjusting the driving part of the automobile, solving the problem that the driver needs to manually adjust the driving part each time, reducing the trouble of the automobile user and providing convenience for the automobile user.
Optionally, the first face detection and recognition network comprises a first face detection network and a first face recognition network;
the first face detection network is used for detecting a face, outputting face classification information, face frame regression information and a plurality of face key point regression information, and outputting a face detection result to the first face identification network;
and the first face recognition network is used for outputting the first face recognition result after processing the first face detection result. The face recognition method has the advantages that the first face detection network is used for detecting the face and outputting face classification information, face frame regression information and a plurality of face key point regression information so as to improve the accuracy of face detection and avoid non-face interference; first face identification network is used for handling first face testing result and output first face identification result, and first face testing network and first face identification network carry out the detection and the discernment of people's face respectively, make first face testing identification network's function is more perfect, and it is more accurate to detect the discernment.
Optionally, the second face detection recognition network includes a second face detection network and a second face recognition network;
the second face detection network is used for acquiring a second face detection result and transmitting the second face detection result to the second face recognition network;
and the second face recognition network is used for judging whether the second face detection result is matched with the prestored face information. The method has the advantages that a second face detection result is obtained through the second face detection network and is transmitted to the second face recognition network; and comparing the second face detection result with the prestored face information through the second face recognition network, and judging whether the second face detection result is matched with the prestored face information so as to determine whether the automobile driver is a user or not, so that the judgment efficiency is high.
Optionally, in step S1, the step of determining the unlocking manner of the automobile according to the first face recognition result includes:
and when the first face detection result is matched with the pre-stored face information, determining that the automobile driver is a user, and automatically unlocking the automobile. The automobile unlocking device has the advantages that the automobile is automatically unlocked after the automobile driver is determined to be the user, so that the efficiency of unlocking the automobile by the user is improved, the user does not need to unlock the automobile by using a key, and the convenience of unlocking the automobile by the user is improved.
Optionally, in step S1, the step of determining the unlocking manner of the automobile according to the first face recognition result includes:
when the first face detection result is not matched with the pre-stored face information, determining that the automobile driver is a guest;
when the guest unlocks the car by the key and successfully unlocks the car, the step S2 is performed.
Optionally, determining that the driver of the car is a guest, further performing the steps of:
and when the guest does not unlock the automobile through the key or does not unlock the automobile and touch the relevant parts of the automobile, an alarm is given. The method has the advantages that after the fact that the automobile driver is the guest is determined, if the guest does not unlock the automobile through the key or does not unlock the automobile and touch relevant parts of the automobile, an alarm is given out to remind a user that the automobile is maliciously unlocked or damaged, and therefore safety of the automobile is improved.
Optionally, in the step S2, the step of comparing the second face detection result with the pre-stored face information to determine the identity of the driver includes:
when the second face detection result is matched with the prestored face information, determining the identity of the automobile driver as the user;
and when the second face detection result is not matched with the pre-stored face information, determining that the automobile driver is a guest, and ending the step S2. The method has the advantages that the step S3 is executed after the driver identity of the automobile is determined to be the user; and after the fact that the automobile driver is the guest is determined, ending the step S2, thereby ending the step in advance without executing the step S3, namely omitting the step of intelligently adjusting the driving part of the automobile, and not recording the adjusted driving part information of the guest, thereby avoiding the storage of excessive one-time information in the information storage library, avoiding information congestion and unnecessary information storage, and ensuring efficient face detection and face recognition of the first face detection recognition module and the second face detection recognition module.
Optionally, the automobile control method based on face recognition further includes step S4: and after each driving, updating the face information of the user to obtain the final face information of the user.
Optionally, in step S3, the step of adjusting the driving component of the automobile according to the driving component adjustment information includes:
comparing the second face detection result with the face information of the last user, and keeping the position of a driving part of the automobile unchanged when the second face detection result is matched with the face information of the last user;
and when the second face detection result is not matched with the face information of the last user and the second face detection result is matched with the prestored face information, extracting the driving part adjusting information corresponding to the prestored face information, and adjusting the driving part of the automobile according to the driving part adjusting information. The method has the advantages that the step 3 is combined with the face information of the last user in the step 4 to judge whether the current driver is the previous user, if the current driver is the previous driver, the position of a driving part of the automobile is kept unchanged, and the energy and the adjusting time of the automobile are saved; if the driver is not the last user but another user, readjusting the driving part; the driving part of the automobile is intelligently controlled and adjusted or not adjusted, so that convenience is provided for a user, when the current user of the automobile and the last user of the automobile are determined to be the same person, the driving part of the automobile is not adjusted, and the adjusting time is saved.
The invention also provides an automobile control system based on face recognition, which comprises:
the first face detection and identification module is arranged on the outer side of the automobile and used for acquiring a first face detection result through a first face detection and identification network and performing comparison operation on the first face detection result and prestored face information to acquire a first face identification result;
the unlocking module is used for determining an unlocking mode of the automobile according to the first face recognition result and successfully unlocking the automobile through the unlocking mode of the automobile;
the second face detection and recognition module is arranged in a cab of the automobile and used for acquiring a second face detection result through a second face detection and recognition network, performing comparison operation on the second face detection result and the prestored face information and performing comparison operation on the second face detection result and the prestored face information to determine the identity of the automobile driver;
and the driving part control module is used for extracting driving part adjusting information corresponding to the prestored face information matched with the user after the identity of the automobile driver is determined as the user, and adjusting the driving part of the automobile according to the driving part adjusting information.
The automobile control system based on face recognition has the beneficial effects that:
acquiring a first face detection result through the first face detection and identification module, and performing comparison operation on the first face detection result and the prestored face information to acquire a first face identification result; the unlocking module determines an unlocking mode of the automobile according to the first face identification result, and safety and rapidness of automobile unlocking are guaranteed; acquiring a second face recognition result through the second face detection recognition module to determine the identity of the automobile driver; after the identity of the automobile driver is determined to be the user, the driving part control module extracts driving part adjusting information corresponding to the prestored face information matched with the user, and adjusts the driving part of the automobile according to the driving part adjusting information. The automobile control system based on the face recognition determines the unlocking mode of the automobile based on the detection and recognition of the face, determines whether a driver is a user or not through the detection and recognition of the face, and intelligently adjusts the driving part of the automobile according to the driving part adjusting information corresponding to the pre-stored face information of the user, so that the time for the user to adjust the driving part is saved, the convenience of the user is improved, and the comfort level and the experience feeling of the user are improved.
The invention also provides equipment which comprises a memory and a processor, wherein the memory stores programs, and when the programs are executed by the processor, the automobile control method based on the face recognition is realized.
The invention also provides a storage medium, wherein a program is stored in the storage medium, and when the program is executed by the processor, the automobile control method based on the face recognition is realized.
The device and the storage medium of the invention have the advantages that:
the safety and the convenience of automobile unlocking are improved, and the driving part of the automobile is intelligently adjusted, so that the problem that the driver needs to manually adjust the driving part when the driver is replaced at every time is solved, and convenience is provided for a user.
Drawings
FIG. 1 is a flowchart of a first implementation manner of an automobile control method based on face recognition according to an embodiment of the present invention;
FIG. 2 is a flowchart of a second implementation manner of an automobile control method based on face recognition according to an embodiment of the present invention;
fig. 3 is a structural diagram of an automobile control system based on face recognition according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. Unless defined otherwise, technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. As used herein, the word "comprising" and similar words are intended to mean that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items.
In view of the problems in the prior art, an embodiment of the present invention provides a face recognition-based automobile control method, and fig. 1 is a flowchart of a first implementation manner of the face recognition-based automobile control method according to the embodiment of the present invention.
In a first embodiment, referring to fig. 1, the automobile control method based on face recognition according to the present invention includes the steps of:
s1: acquiring a first face detection result through a first face detection and identification network, performing comparison operation on the first face detection result and prestored face information to acquire a first face identification result, and determining an unlocking mode of the automobile according to the first face identification result;
s2: after the automobile is successfully unlocked in the automobile unlocking mode, a second face detection result is obtained through a second face detection and recognition network, and comparison operation is carried out on the second face detection result and the prestored face information to determine the identity of an automobile driver;
s3: and after the identity of the automobile driver is determined as the user, extracting the driving part adjusting information corresponding to the prestored face information matched with the user, and adjusting the driving part of the automobile according to the driving part adjusting information.
In some embodiments, the pre-stored face information and the driving component adjustment information are saved by a stored information base;
when the users of the automobile are unique, the number of the pre-stored face information of the users in the storage information base is one, and the number of the pre-stored face information of the users and the number of the adjusting information of the driving part are both one;
when a plurality of automobile users are available, such as the automobile users comprise an automobile owner and an owner, or the company public vehicle users comprise a plurality of company employees, the number of the pre-stored face information of the users in the storage information base is more than two, and the number of the pre-stored face information of the users and the number of the driving part adjusting information are more than two; and the prestored face information of each user corresponds to the driving part adjusting information of the user one by one.
In some alternative embodiments, the driving components of the automobile include a cabin seat, a center rear view mirror, a left side rear view mirror, a right side rear view mirror, and a steering wheel of the automobile;
the driving part adjustment information includes adjustment information of an angle or height of a seat, adjustment information of an angle of a center rear view mirror, adjustment information of an angle and a fold of a left side rear view mirror, adjustment information of an angle and a fold of a right side rear view mirror, and adjustment information of a height of a steering wheel.
The automobile control method based on the face recognition has the advantages that: the invention improves the safety and convenience of automobile unlocking by detecting the face information and determining the unlocking mode of the automobile; the driver identity of the automobile is determined according to the comparison result of the face similarity and the similarity threshold, if the automobile driver is a user, the adjustment information of the driving part is determined according to the internal face information matched with the user, so that the driving part of the automobile is intelligently adjusted, the problem that the driver needs to manually adjust the driving part when the driver is replaced every time is solved, the trouble of the automobile user is reduced, and convenience is provided for the automobile user.
Fig. 2 is a flowchart of a second implementation manner of the automobile control method based on face recognition according to the embodiment of the invention.
In a second embodiment, referring to fig. 2, the automobile control method based on face recognition according to the present invention further performs step S0 before performing step S1 on the basis of the above steps S1 to S3:
the face information of the user is detected and stored to serve as prestored face information, and the use information of the user on the driving part is recorded to obtain the adjustment information of the driving part. The method has the advantages that the face information of a user is detected and the prestored face information is stored, and the driving part adjusting information of the user is recorded, so that reference information is provided for the face comparison operation of the subsequent first face identification network and the second face identification network;
referring to fig. 2, after performing step S3, step S4 is also performed:
and after each driving, updating the face information of the user to obtain the final face information of the user.
In some optional embodiments, a first face detection recognition module and a second face detection recognition module are provided, the first face detection recognition module is provided with the first face detection recognition network, and the second face detection recognition module is provided with the second face detection recognition network.
As an optional implementation manner of the present invention, the first face detection network is configured to detect a face and output face classification information, face frame regression information, and a plurality of face key point regression information, and the first face detection network is further configured to output a face detection result to the first face identification network;
and the first face recognition network is used for outputting the first face recognition result after processing the first face detection result. The first face detection network and the first face recognition network are obtained through training, and the first face detection network is used for detecting faces and outputting face classification information, face frame regression information and a plurality of face key point regression information, so that the accuracy of face detection is improved, and non-face interference is avoided; first face identification network is used for handling first face testing result and output first face identification result, and first face testing network and first face identification network carry out the detection and the discernment of people's face respectively, make first face testing identification network's function is more perfect, and it is more accurate to detect the discernment.
As an optional implementation manner of the present invention, the second face detection and recognition network includes a second face detection network and a second face recognition network;
the second face detection network is used for acquiring a second face detection result and transmitting the second face detection result to the second face recognition network;
and the second face recognition network is used for judging whether the second face detection result is matched with the prestored face information. The method has the advantages that a second face detection result is obtained through the second face detection network and is transmitted to the second face recognition network; and comparing the second face detection result with the prestored face information through the second face recognition network, and judging whether the second face detection result is matched with the prestored face information so as to determine whether the automobile driver is a user or not, so that the judgment efficiency is high.
In some embodiments of the invention, the training of the first face detection network comprises:
providing a face detection Mnet network, wherein the face detection Mnet network is an improved version based on a face recognition Retinaface network; the difference between the face detection Mnet network and the face recognition Retinaace network is that a main network of the face detection Mnet network uses mobilene to lighten a model, and an SSH detection module consisting of an SSH (Single Stage Headless) context module is added at the position of a tail detection head of the face detection Mnet network; the input size of the face detection Mnet network is 3-channel RGB image, and the output comprises three parts: face classification information, face frame regression information and a plurality of face key point regression information;
under a noise framework, inputting 20.4 thousands of images as a training data set and 3.5 thousands of data as a verification set into the face detection Mnet network, and training the face detection Mnet network by using a Stochastic Gradient Descent (SGD) optimizer, wherein training parameters are set as follows: the momentum (momentum) of the SGD optimizer is 0.9, the weight decay (weights decay) is 0.0005, the batch size (batch size) is 8 × 4, the initial learning rate is 0.001, the learning rate is modified to 0.01 after 5 epochs are completed, and finally the modification rate is modified to 0.001 at the 55 th epoch and the 68 th epoch, respectively.
It can be said that when all training data sets are input into the network model, a complete training is performed, and this process is called an epoch.
In some optional embodiments of the present invention, the face recognition network of the present invention employs a face recognition MobileFaceNet network, and the face recognition MobileFaceNet network employs MobileNetv2 as a baseline model.
In some specific embodiments of the present invention, the training of the first face recognition network specifically comprises:
before training the face recognition mobilefenet network, cleaning a Glint360K public data set, namely, inputting original 361K data which is reduced to 215K data into the face recognition mobilefenet network for training from the beginning, wherein the training parameters comprise:
the loss function adopts a face recognition loss function (ArcFace loss), momentum of an SGD optimizer is 0.9, weight hierarchy of a global operation layer is 4e-4, weight hierarchies of other layers except the global operation layer are 4e-5, batch size is 512, initial learning rate is 0.1, the learning rate is modified to be 0.01 when iteration times (iterations) of 36K, 52K and 58K are respectively carried out, and the learning rate is still 0.1 in the time periods except the iteration times of 36K, 52K and 58K; the face recognition MobileFaceNet network is trained through an SGD optimizer, and training is stopped when training reaches 60 Kiterions.
It can be said that 4e-4 corresponds to 4X 10-44e-5 corresponds to 4X 10-5。
In some optional embodiments of the present invention, the second face detection and recognition network includes a second face detection network and a second face recognition network, and since the training steps of the second face detection network and the first face detection network are the same, the training steps of the second face recognition network and the first face recognition network are the same, and thus are not repeated.
As an optional implementation manner of the present invention, in step S1, the step of determining an unlocking manner of the automobile according to the first face recognition result includes:
and when the first face detection result is matched with the pre-stored face information, determining that the automobile driver is a user, and automatically unlocking the automobile. The automobile unlocking device has the advantages that the automobile is automatically unlocked after the automobile driver is determined to be the user, so that the efficiency of unlocking the automobile by the user is improved, the user does not need to unlock the automobile by using a key, and the convenience of unlocking the automobile by the user is improved.
As an optional implementation manner of the present invention, the step of determining an unlocking manner of the automobile according to the first face recognition result further includes:
when the first face detection result is not matched with the pre-stored face information, determining that the automobile driver is a guest;
after determining that the automobile driver is a guest, further performing the following steps:
when the guest unlocks the car by the key and successfully unlocks the car, executing the step S2;
and when the guest does not unlock the automobile through the key or does not unlock the automobile and touch the relevant parts of the automobile, giving an alarm. The method has the advantages that after the automobile driver is determined to be a guest, if the guest does not unlock the automobile through a key or does not unlock the automobile and touch related parts of the automobile, an alarm is given out to remind a user that the automobile is maliciously unlocked or damaged, and therefore the safety of the automobile is improved.
In some optional specific embodiments, the specific step of step S1 includes:
before a driver gets on the vehicle, the first face detection and identification module adjusts the image size of the current frame of the video stream into an initial image with the resolution of 320 multiplied by 320, and inputs the initial image into the face detection Mnet network, and finally the face detection Mnet network outputs all face classification information, face frames rectbox of all face positions and 5 key points of the face;
the first face detection and identification module cuts out a face image ROIimage from the initial image according to the face frame rectbox, and adjusts the resolution of the face image ROIimage to be 112 multiplied by 112 to obtain a faceimg image, wherein the first face detection result comprises the faceimg image;
it can be said that ROIimage is an abbreviation of region of interest image, wherein the text name is region of interest image, in the field of image processing, a region to be processed is outlined from a processed image in a square, circle, ellipse and irregular figure to be called region of interest; the faceimg image is an img format of a face image.
And inputting the faceimg image into the face recognition MobileFaceNet network, and outputting the similarity value between the faceimg image and each piece of prestored face information in the storage information base by the face recognition MobileFaceNet network. The first face recognition result comprises similarity values of the faceimg image and each piece of pre-stored face information in the stored information base.
The first face detection and identification module outputs a plurality of similarity values to the system, and the system performs the following operations:
the system sorts the similarity values to obtain the maximum value max of all the similarity values, when the system judges that max is larger than or equal to 0.6, the faceimg image is successfully matched with the prestored face information with the maximum similarity value, the prestored face information corresponding to the maximum value max of the similarity values is determined to be matched with the face information of the user, the system determines that the automobile driver is the user, and then the system sends out an automobile unlocking instruction to automatically unlock the automobile;
when the system judges that max is less than 0.6, the faceimg image is judged to be not successfully matched with the prestored face information in the storage information base, and the fact that the automobile driver is a guest is determined, and the guest can unlock the automobile only through a key is determined;
if the guest does not unlock the vehicle by the key, or does not unlock the vehicle and touches the door or pulls the door handle, the system sends an alarm to remind the owner of the vehicle to try to steal or destroy the vehicle.
As an optional implementation manner of the present invention, in step S2, the step of performing a comparison operation on the second face detection result and the pre-stored face information to determine the identity of the driver of the automobile includes:
when the second face detection result is matched with the prestored face information, determining the identity of the automobile driver as the user;
and when the second face detection result is not matched with the pre-stored face information, determining that the automobile driver is a guest, and ending the step S2. Advantageously, step S3 is performed when the driver identity of the vehicle is determined to be the user; after the automobile driver is determined to be a guest, the second face detection and recognition step is finished, so that the step of intelligently adjusting the driving part of the automobile is omitted, the information of the adjusted driving part of the guest cannot be recorded, excessive one-time information is prevented from being stored in the information storage library, information congestion and unnecessary information storage are avoided, and efficient face detection and face recognition of the first face detection and recognition module and the second face detection and recognition module are guaranteed.
As an alternative embodiment of the present invention, in step S3, the step of adjusting the driving component of the vehicle according to the driving component adjustment information includes:
comparing the second face detection result with the face information of the last user, and keeping the position of a driving part of the automobile unchanged when the second face detection result is matched with the face information of the last user;
and when the second face detection result is not matched with the face information of the last user and the second face detection result is matched with the prestored face information, extracting the driving part adjusting information corresponding to the prestored face information, and adjusting the driving part of the automobile according to the driving part adjusting information. The method has the advantages that the step 3 is combined with the face information of the last user in the step 4 to judge whether the current driver is the previous user, if the current driver is the previous driver, the position of a driving part of the automobile is kept unchanged, and the energy and the adjusting time of the automobile are saved; readjusting the driving member if the driver is not the last user but another user; the driving part of the automobile is intelligently controlled and adjusted or not adjusted, so that convenience is provided for a user, when the current user of the automobile and the last user of the automobile are determined to be the same person, the position of the driving part of the automobile is kept unchanged, and the adjusting time is saved.
In some optional specific embodiments, the specific steps of steps S2, S3, and S4 include:
(1) the second face detection and identification module adjusts the image size of the current frame of the video stream into an initial image with the resolution of 320 multiplied by 320, inputs the initial image into the face detection Mnet network, and finally the face detection Mnet network outputs all face classification information, face frames rectbox of all face positions and 5 key points of the face;
then the second face detection and recognition module cuts out a face image ROIimage from the initial image according to the face frame rectbox, and adjusts the resolution of the face image ROIimage to be 112 multiplied by 112 to obtain a faceimg image, wherein the second face recognition result comprises the faceimg image;
and inputting the faceimg image into the face recognition MobileFaceNet network, and outputting the similarity value between the faceimg image and each piece of prestored face information in the storage information base by the face recognition MobileFaceNet network. And the second face recognition result comprises the similarity value between the faceimg image and each piece of pre-stored face information in the stored information base.
(2) After the second face detection and recognition module outputs a plurality of similarity values, the system performs the following operations:
after the system receives the similarity values, the system sorts the similarity values to obtain a maximum value max of all the similarities, and the system compares max with a similarity threshold, which is set to 0.6 in some embodiments. When the system judges that max is less than 0.6, the fact that the faceimg image is not successfully matched with the prestored face information in the storage information base is judged, the system determines that the automobile driver is the guest, the system does not store the face information of the guest and the adjustment information of the driving part in the driving process of the guest, and after driving is finished, the system automatically adjusts the position of the driving part to be the position of the driving part corresponding to the adjustment information of the driving part of the first user, so that the next user can conveniently drive the automobile;
when the system judges that max is more than or equal to 0.6, judging that the faceimg image is successfully matched with the prestored face information with the maximum similarity value, determining that the automobile driver is a user, and after determining that the automobile driver is the user, performing the following steps:
the system compares the faceimg image with the face information of the last user, if the similarity between the faceimg image and the face information of the last user is more than 0.6, the faceimg image is matched with the face information of the last user, the system determines that the driver of the automobile and the driver of the automobile at the last time are the same user, and the system controls the position of a driving part of the automobile to be kept unchanged;
if the similarity between the faceimg image and the face information of the last user is less than 0.6, the faceimg image is not matched with the face information of the last user, and the system determines that the driver of the automobile is different from the driver of the automobile at the last time; and when the second face detection result is matched with the prestored face information in the face library, determining driving part adjusting information according to the prestored face information matched with the current user of the automobile, and adjusting the driving part of the automobile by the system according to the driving part adjusting information so as to adjust the position of the driving part to the position to which the current user is accustomed.
(3) And after the user drives the vehicle every time, the system updates the face information of the user who drives the vehicle finally according to the face information detected and identified by the second face detection and identification module so as to obtain the face information of the user finally.
In some embodiments, the system is the face recognition-based automobile control system of the invention.
In some optional embodiments, when the stored information base stores the pre-stored face information of the user, but does not store the driving component adjustment information corresponding to the pre-stored face information, for example, when the user drives the car for the first time, the driving component adjustment automatic recording step is started, and the step includes:
starting timing from the moment when the user adjusts the driving part, and if the user keeps the adjusted position of the driving part within the time t which is more than or equal to 15-20min, namely the user does not adjust the position of the driving part within the continuous time of 15-20min, taking the adjusted position of the driving part as the driving part adjusting information corresponding to the prestored face information;
if the user readjusts the position of the steering member within a time period t <15-20min, i.e. the user readjusts the position of the steering member within a continuous time period of less than 15-20min, the system does not update the steering member adjustment information of the user, and the holding time t is updated.
The invention also provides a face recognition-based automobile control system, and FIG. 3 is a structural diagram of the face recognition-based automobile control system according to the embodiment of the invention.
Referring to fig. 3, the face recognition-based automobile control system of the present invention includes:
the first face detection and identification module 1 is arranged on the outer side of the automobile and used for acquiring a first face detection result through a first face detection and identification network and performing comparison operation on the first face detection result and prestored face information to acquire a first face identification result;
the unlocking module 3 is used for determining an unlocking mode of the automobile according to the first face recognition result and successfully unlocking the automobile through the unlocking mode of the automobile;
the second face detection and recognition module 2 is installed in the cab of the automobile and used for acquiring a second face detection result through a second face detection and recognition network, performing comparison operation on the second face detection result and the prestored face information and performing comparison operation on the second face detection result and the prestored face information to determine the identity of the automobile driver;
and the driving part control module 4 is used for extracting driving part adjusting information corresponding to the prestored face information matched with the user after the identity of the automobile driver is determined as the user, and adjusting the driving part of the automobile according to the driving part adjusting information.
The automobile control system based on the face recognition has the advantages that: detect the people face and obtain first face identification result through first face detection identification module 1 to confirm the unblock mode of car, and whether the driver is the user through the detection discernment of second face detection identification module 2 to the people face, driver part control module 4 is according to the driver part adjustment information that user's prestore face information corresponds, the driver part of intelligent regulation car, the time of user regulation driver part has been saved, user's convenience has been improved, user's comfort level and experience are felt have been improved.
In some embodiments, referring to fig. 3, the automobile control system based on face recognition further includes a recording module 5, configured to detect face information of a user and store the face information as pre-stored face information, and record usage information of the driving component by the user to obtain driving component adjustment information.
In some embodiments, referring to fig. 3, the recording module 5 includes a face entry unit (not shown in the figure, a driving component usage information and status information detection unit (not shown in the figure) and a storage information base 50, the face entry unit detects a face to obtain user face information, the storage information base 50 stores the user face information as the pre-stored face information, the driving component usage information and status information detection unit detects the user usage information and status information of the driving component during driving of the vehicle, the storage information base 50 stores the driving component usage information and status information as the driving component adjustment information, and the pre-stored face information of each user corresponds to the driving component adjustment information of the user.
In some optional specific embodiments, the first face detection and recognition module 1 is installed outside the automobile, and specifically, the first face detection and recognition module 1 is disposed at a position where the ground clearance of the left B pillar or the right B pillar of the automobile is 160cm, so that the first face detection and recognition module 1 performs face detection and recognition on a driver located outside the automobile to determine an unlocking manner of the automobile.
In some optional specific embodiments, the second face detection and recognition module 2 is installed inside the automobile, specifically, the second face detection and recognition module 2 is installed in a cab of the automobile so as to detect and recognize a face of a driver, and after the driver enters the cab or sits on a driver seat, the second face detection and recognition module 2 performs face detection and recognition on the face of the driver, so as to determine whether to adjust the driving component.
As an optional implementation manner of the present invention, a first face detection network and a first face recognition network are arranged in the first face detection recognition module 1, the first face detection network is configured to detect a face and output face classification information, face frame regression information and a plurality of face key point regression information, and the first face detection network is further configured to output a face detection result to the first face recognition network;
and the first face recognition network is used for outputting the first face recognition result after processing the first face detection result.
In some optional embodiments, the first face detection network employs the face detection network described above, and the first face recognition network employs the face recognition network described above.
As an optional implementation manner of the present invention, a second face detection network and a second face recognition network are arranged in the second face detection recognition module 2, where the second face detection network is configured to obtain a second face detection result and transmit the second face detection result to the second face recognition network;
and the second face recognition network is used for judging whether the second face detection result is matched with the prestored face information.
As an optional implementation manner of the present invention, referring to fig. 2, the automobile control system based on face recognition of the present invention further includes an alarm module 6, wherein after the first face detection recognition module 1 recognizes that the driver of the automobile is a guest, if the guest unlocks the automobile by a key, the alarm module 6 is not started; if the guest does not unlock the car by a key or touches or pulls car parts such as a car door and a car door handle, the alarm module 6 starts an alarm to give an alarm to remind a car user.
Referring to fig. 2, in some alternative embodiments of the present invention, the operation steps of the automobile control system based on face recognition are:
(1) when the first face detection and recognition module 1 detects a face, performing primary face detection and recognition, recording face information of the first face detection and recognition to obtain a first face detection result, matching the first face detection result with prestored face information in the stored information base 50, and if the first face detection result is unsuccessfully matched with the prestored face information, determining that the driver of the automobile is a guest who can unlock the automobile only through a key; if the guest does not unlock the car by the key or touches or pulls car doors, car door handles and other car parts, the alarm module 6 starts alarming and gives an alarm;
if the first face detection result is successfully matched with the prestored face information, determining that a driver waiting for the automobile is a user, and controlling the automobile lock of the automobile to be opened by the unlocking module 3 so as to automatically unlock the automobile;
(2) after the automobile driver successfully unlocks the automobile and enters the cab, the second face detection and recognition module 2 carries out secondary face detection and recognition on a face, the face information of the driver to be detected is recorded to obtain a second face detection result, the second face detection result is matched with the prestored face information, if the second face detection result is failed to be matched with the prestored face information, the driver to be detected is determined to be a guest, the driving part control module 4 does not adjust a driving part at the moment, the position of the driving part of the automobile is kept unchanged, and the face information and the driving part adjustment information of the guest are not recorded or stored in the process of driving the automobile by the guest;
if the second face detection result is successfully matched with the prestored face information, determining that the driver waiting for the automobile is a user;
(3) after the automobile driver is determined to be a user, if the corresponding driving part adjusting information of the user is not stored in the storage information base 50, the recording module 5 starts and executes the automatic recording and storing step of the driving part adjusting to record the driving part adjusting information of a new user, stores the recorded driving part adjusting information into the storage information base 50, and enables the driving part adjusting information to be correspondingly matched with the prestored face information of the user; if the stored information base 50 stores the corresponding driving component adjustment information of the user, the face information of the current user and the face information of the last user are compared through the second face detection and recognition module 2, if the face information of the current user and the face information of the last user are successfully matched, the current user and the last user of the automobile are the same person, and at the moment, the driving component control module 4 keeps the position of the driving component unchanged;
if the matching of the face information of the current user and the face information of the last user fails, comparing the face information of the current user with the prestored face information in the stored information base 50 through the second face detection and recognition module 2, determining the prestored face information matched with the current user, and then determining the driving part adjusting information corresponding to the prestored face information, wherein at the moment, the driving part control module 4 adjusts the driving part of the automobile according to the driving part adjusting information so as to adjust the driving part to the position to which the current user is accustomed;
(4) after each driving, if the second face detection and recognition module 2 detects and recognizes that the automobile driver is a user, the recording module 5 updates the face information of the last user according to the face information detected and recognized by the second face detection and recognition module 2, that is, the face information of the last user of the automobile is stored in the storage information base 50 as the face information of the last user.
The invention also provides equipment which comprises a memory and a processor, wherein the memory stores programs, and when the programs are executed by the processor, the automobile control method based on the face recognition is realized.
The invention also provides a storage medium, wherein the storage medium stores a program, and when the program is executed by the processor, the automobile control method based on the face recognition is realized.
The advantages of the device and the storage medium of the invention are: the safety and the convenience of automobile unlocking are improved, and the driving part of the automobile is intelligently adjusted, so that the problem that the driver needs to manually adjust the driving part when the driver is replaced at every time is solved, and convenience is provided for a user.
Although the embodiments of the present invention have been described in detail hereinabove, it is apparent to those skilled in the art that various modifications and variations can be made to these embodiments. However, it is to be understood that such modifications and variations are within the scope and spirit of the present invention as set forth in the following claims. Moreover, the invention as described herein is capable of other embodiments and of being practiced or of being carried out in various ways.
Claims (10)
1. A car control method based on face recognition is characterized by comprising the following steps:
s1: acquiring a first face detection result through a first face detection and identification network, performing comparison operation on the first face detection result and prestored face information to acquire a first face identification result, and determining an unlocking mode of the automobile according to the first face identification result;
s2: after the automobile is successfully unlocked in the automobile unlocking mode, acquiring a second face detection result through a second face detection and recognition network, and performing comparison operation on the second face detection result and the prestored face information to determine the identity of the automobile driver;
s3: after the identity of the automobile driver is determined as a user, extracting driving part adjusting information corresponding to prestored face information matched with the user, and adjusting the driving part of the automobile according to the driving part adjusting information, wherein the method specifically comprises the following steps:
comparing the second face detection result with the face information of the last user, and keeping the position of a driving part of the automobile unchanged when the second face detection result is matched with the face information of the last user;
when the second face detection result is not matched with the face information of the last user and the second face detection result is matched with the prestored face information, extracting the driving part adjusting information corresponding to the prestored face information, and adjusting the driving part of the automobile according to the driving part adjusting information;
s4: and after each driving, updating the face information of the user to obtain the final face information of the user.
2. The face recognition-based vehicle control method of claim 1, wherein the first face detection recognition network comprises a first face detection network and a first face recognition network;
the first face detection network is used for detecting a face, outputting face classification information, face frame regression information and a plurality of face key point regression information, and outputting a face detection result to the first face identification network;
and the first face recognition network is used for outputting the first face recognition result after processing the first face detection result.
3. The face recognition-based automobile control method according to claim 1, wherein the second face detection recognition network includes a second face detection network and a second face recognition network;
the second face detection network is used for acquiring a second face detection result and transmitting the second face detection result to the second face recognition network;
and the second face recognition network is used for judging whether the second face detection result is matched with the prestored face information.
4. The method for controlling a vehicle based on face recognition according to claim 1, wherein the step of determining the unlocking manner of the vehicle according to the first face recognition result in step S1 includes:
and when the first face detection result is matched with the pre-stored face information, determining that the automobile driver is a user, and automatically unlocking the automobile.
5. The method for controlling a vehicle based on face recognition according to claim 1, wherein the step of determining the unlocking manner of the vehicle according to the first face recognition result in step S1 includes:
when the first face detection result is not matched with the pre-stored face information, determining that the automobile driver is a guest;
when the guest unlocks the car by the key and successfully unlocks the car, the step S2 is performed.
6. The method as claimed in claim 5, wherein after determining that the driver is a guest, further performing the steps of:
and when the guest does not unlock the automobile through the key or does not unlock the automobile and touch the relevant parts of the automobile, an alarm is given.
7. The method as claimed in claim 1, wherein the step S2 of comparing the second face detection result with the pre-stored face information to determine the identity of the driver comprises:
when the second face detection result is matched with the prestored face information, determining the identity of the automobile driver as the user;
and when the second face detection result is not matched with the pre-stored face information, determining that the automobile driver is a guest, and ending the step S2.
8. An automobile control system based on face recognition is characterized by comprising:
the first face detection and recognition module is arranged on the outer side of the automobile and used for acquiring a first face detection result through a first face detection and recognition network and performing comparison operation on the first face detection result and prestored face information to acquire a first face recognition result;
the unlocking module is used for determining an unlocking mode of the automobile according to the first face recognition result and successfully unlocking the automobile through the unlocking mode of the automobile;
the second face detection and recognition module is arranged in a cab of the automobile and used for acquiring a second face detection result through a second face detection and recognition network, performing comparison operation on the second face detection result and the prestored face information and performing comparison operation on the second face detection result and the prestored face information to determine the identity of the automobile driver;
and the driving part control module is used for extracting driving part adjusting information corresponding to the prestored face information matched with the user after the identity of the automobile driver is determined as the user, and adjusting the driving part of the automobile according to the driving part adjusting information.
9. An apparatus comprising a memory and a processor, wherein the memory stores a program, and when the program is executed by the processor, the method for controlling an automobile based on face recognition according to any one of claims 1 to 7 is implemented.
10. A storage medium, characterized in that the storage medium stores a program, and when the program is executed by a processor, the method for controlling an automobile based on face recognition according to any one of claims 1 to 7 is implemented.
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