Face unlocking methods, devices and equipment

Abstract

This application provides a face unlocking method, apparatus, and device. It acquires N first images of a user to be identified, each acquired by N first image acquisition devices; and acquires a dynamic image of the user to be identified, acquired by a second image acquisition device. If a comparison between one of the N first images and a pre-stored image is successful, the dynamic image of the user is compared with the pre-stored dynamic image. In response to a successful comparison between the dynamic image of the user and the pre-stored dynamic image, the visual screen connected to the control device is unlocked. This application can accurately recognize faces and unlock the screen of a visual screen even in complex environments, achieving the effect of unlocking a visual screen based on face recognition.

Description

Technical Field

[0001] This application relates to the field of facial recognition technology, and in particular to a facial unlocking method, apparatus, and device. Background Technology

[0002] Today, facial recognition technology is used in many fields, such as unlocking screens based on facial recognition.

[0003] In existing technologies, facial recognition-based screen unlocking methods can be applied to mobile devices. Mobile devices can capture facial images using their cameras and then unlock their screens based on those images.

[0004] However, the above method, which relies solely on facial images to unlock the screen, is unsuitable for unlocking large visual displays. For example, large visual displays are often deployed in complex environments such as exhibitions and trade shows, involving numerous users. Therefore, relying solely on facial images for unlocking makes the process inaccurate. Summary of the Invention

[0005] This application provides a face unlocking method, apparatus, and device to solve the problem that unlocking a large visual screen based solely on a face image is inaccurate due to the complex on-site environment in which the large visual screen is located.

[0006] In a first aspect, this application provides a face unlocking method, the method being applied to a control device, the method comprising:

[0007] The system acquires N first images of the user to be identified, each acquired by a different first image acquisition device. Each first image is acquired by a different first preset position, and the first image is a facial image of the user to be identified. The system also acquires a user dynamic image of the user to be identified, acquired by a second image acquisition device, located at a second preset position. The user dynamic image is a body movement image of the user to be identified. N is a positive integer greater than 1.

[0008] If it is determined that one of the N first images is successfully matched with a pre-stored image, then the user dynamic image is compared with the pre-stored dynamic image; wherein, the pre-stored image is a pre-stored image of the user's face; and the pre-stored dynamic image is a pre-stored image of the user's body behavior.

[0009] If the comparison between the user's dynamic image and the pre-stored dynamic image is successful, the visualization screen connected to the control device will be unlocked.

[0010] In one example, if it is determined that a comparison between one of the N first images and a pre-stored image is successful, then the user dynamic image is compared with the pre-stored dynamic image, including:

[0011] Repeat the following steps until one of the N first images is successfully compared with the pre-stored image:

[0012] First facial information is extracted from the i-th first image; wherein the first facial information represents the light intensity information of the environment in which the user to be identified is located; i is a positive integer greater than or equal to 1 and less than or equal to N;

[0013] Based on the first facial information and the first pre-stored facial information, the i-th first image is adjusted to obtain the second image corresponding to the i-th first image; wherein, the first pre-stored facial information represents the pre-stored light intensity information of the user's environment;

[0014] If it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful, then the user dynamic image is compared with the pre-stored dynamic image;

[0015] If it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image fails, then the value of i is incremented by 1.

[0016] In one example, the method further includes:

[0017] The second image corresponding to the i-th first image is compared with the pre-stored image to obtain a first matching value; wherein, the first matching value represents the degree of matching between the second image and the pre-stored image;

[0018] If the first matching value is greater than the first preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful;

[0019] If the first matching value is less than or equal to the first preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed.

[0020] In one example, before comparing the user's animated image with a pre-stored animated image, the process includes:

[0021] Second facial information and third facial information are extracted from the second image corresponding to the i-th first image; wherein, the second facial information represents the facial feature information of the user to be identified; and the third facial information represents the micro-expression information of the user to be identified.

[0022] If it is determined that the comparison between the second facial information and the second pre-stored facial information is successful, and the comparison between the third facial information and the third pre-stored facial information is successful, then the step of comparing the user's dynamic image with the pre-stored dynamic image is executed; wherein, the second pre-stored facial information is the pre-stored facial feature information of the user; and the third pre-stored facial information is the pre-stored micro-expression information of the user.

[0023] In one example, the method further includes:

[0024] The second facial information is compared with the second pre-stored facial information to obtain a second matching value; wherein, the second matching value represents the degree of matching between the second facial information and the second pre-stored facial information;

[0025] If the second matching value is greater than the second preset threshold, then the comparison between the second facial information and the second pre-stored facial information is determined to be successful.

[0026] If the second matching value is less than or equal to the second preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed.

[0027] In one example, the method includes:

[0028] The third facial information is compared with the third pre-stored facial information to obtain a third matching value; wherein, the third matching value represents the degree of matching between the third facial information and the third pre-stored facial information;

[0029] If the third matching value is greater than the third preset threshold, then the comparison between the third facial information and the third pre-stored facial information is determined to be successful;

[0030] If the third matching value is less than or equal to the third preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed.

[0031] In one example, the method further includes:

[0032] The user's dynamic image is compared with the pre-stored dynamic image to obtain a fourth matching value; wherein, the fourth matching value represents the degree of matching between the user's dynamic image and the pre-stored dynamic image;

[0033] If the fourth matching value is greater than the fourth preset threshold, then the comparison between the user's dynamic image and the pre-stored dynamic image is determined to be successful.

[0034] If the fourth matching value is less than or equal to the fourth preset threshold, it is determined that the comparison between the user dynamic image and the pre-stored dynamic image has failed, and the step of acquiring N first images of the user to be identified acquired by N first image acquisition devices is executed again.

[0035] In one example, the method further includes:

[0036] In response to a face unlock request, the step of acquiring N first images of the user to be identified, each acquired by a first image acquisition device, is performed; wherein the face unlock request is used to instruct face unlock to be performed.

[0037] In one example, the method further includes:

[0038] If it is determined that the N first image acquisition devices and the second image acquisition device are all in normal working condition, then the step of acquiring the N first images of the user to be identified acquired by the N first image acquisition devices is executed.

[0039] In one feasible implementation, the control device connects to multiple image acquisition devices located at different positions. Multiple image acquisition devices acquire facial images of the user to be identified, while one device acquires dynamic body movement images of the user. The control device can obtain the acquired images of the user from all the image acquisition devices. It then extracts a facial image from the multiple facial images and compares it with pre-stored user facial images. If the comparison is successful, the acquired body movement image of the user to be identified is compared with the pre-stored body movement image. If the comparison fails... If the comparison fails, a new face image and body image are extracted from the multiple face images and compared again until a face image is successfully compared. If the comparison fails, a new face image and body image are obtained from the image acquisition device and compared again until a comparison is successful, thus achieving the effect of unlocking the visual screen based on face recognition.

[0040] Secondly, this application provides a face unlocking device, comprising:

[0041] The acquisition unit is configured to acquire N first images of the user to be identified, each acquired by a first image acquisition device, wherein each first image is acquired by a single image acquisition device, the N first image acquisition devices are located at different first preset positions, and the first image is a facial image of the user to be identified; and to acquire a user dynamic image of the user to be identified, acquired by a second image acquisition device, wherein the second image acquisition device is located at a second preset position, and the user dynamic image is a body behavior image of the user to be identified; N is a positive integer greater than 1;

[0042] The first determining unit is configured to compare the user dynamic image with the pre-stored dynamic image if a successful comparison is found between one of the N first images and a pre-stored image; wherein the pre-stored image is a pre-stored image of the user's face; and the pre-stored dynamic image is a pre-stored image of the user's body movements.

[0043] The unlocking unit is used to unlock the large visual screen connected to the control device in response to a successful comparison between the user's dynamic image and a pre-stored dynamic image.

[0044] Thirdly, embodiments of this application provide an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0045] The memory stores computer-executed instructions;

[0046] The processor executes computer execution instructions stored in the memory to perform the method described in the first aspect.

[0047] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in the first aspect.

[0048] Fifthly, embodiments of this application provide a computer program product comprising: a computer program stored in a readable storage medium, wherein at least one processor of an electronic device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to cause the electronic device to perform the method described in the first aspect.

[0049] This application provides a face unlocking method, apparatus, and device. The method acquires N first images of a user to be identified, each captured by one of N first image acquisition devices. Each first image is acquired by one of the N first image acquisition devices, and the N first image acquisition devices are located at different first preset positions. The first image is a face image of the user to be identified. The method also acquires a user dynamic image of the user to be identified, captured by a second image acquisition device, located at a second preset position. The user dynamic image is a body behavior image of the user to be identified. N is a positive integer greater than 1. If a comparison between one of the N first images and a pre-stored image is successful, the user dynamic image is compared with the pre-stored dynamic image. The pre-stored image is a pre-stored face image of the user. The pre-stored dynamic image is a pre-stored body behavior image of the user. In response to a successful comparison between the user dynamic image and the pre-stored dynamic image, a large visual screen connected to the control device is unlocked. First, the control device connects to multiple image acquisition devices located in different positions. Multiple image acquisition devices acquire facial images of the user to be identified, while one device acquires dynamic body movement images of the user. The control device can obtain the acquired images of the user from all the image acquisition devices. From these multiple facial images, a single facial image is extracted and compared with pre-stored user facial images. If the comparison is successful, the acquired body movement image of the user to be identified is compared with pre-stored user body movement images. If the comparison is successful... If the comparison fails, another face image is extracted from multiple face images and compared again. After comparing the acquired body behavior image of the user to be identified with the pre-stored body image of the user, if the comparison between the acquired body behavior image of the user to be identified and the pre-stored body image of the user is successful, the screen of the visualization screen connected to the control device can be unlocked. If the comparison between the acquired body behavior image of the user to be identified and the pre-stored body image of the user is unsuccessful, a new face image and body behavior image to be identified are acquired from the image acquisition device and compared again until the comparison is successful, thus achieving the effect of unlocking the visualization screen based on face recognition. Attached Figure Description

[0050] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0051] Figure 1 A flowchart illustrating a face unlocking method provided in an embodiment of this application;

[0052] Figure 2 A flowchart illustrating another face unlocking method provided in an embodiment of this application;

[0053] Figure 3 This is a schematic diagram of the structure of a face unlocking device provided in an embodiment of this application;

[0054] Figure 4 This is a schematic diagram of another face unlocking device provided in an embodiment of this application;

[0055] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0056] Figure 6 This is a block diagram illustrating an electronic device according to an exemplary embodiment.

[0057] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0058] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0059] In existing technologies, facial recognition-based screen unlocking methods can be applied to mobile devices. Mobile devices can capture facial images using their cameras and then unlock their screens based on those images.

[0060] In one example, a face unlock application installed on a mobile terminal device quickly identifies a person and unlocks the large screen. For example, it collects the face image of the user to be unlocked; selects a pre-stored face image from the face unlock database for face unlock comparison based on at least one scene information of the face image; at least determines whether the feature information of the face image matches the feature information of the pre-stored face image; when the feature information of the face image matches the feature information of the pre-stored face image, the mobile terminal is unlocked.

[0061] However, the above methods, which rely solely on facial images to unlock the screen, are unsuitable for unlocking large visual displays. For example, large visual displays are often deployed in exhibition halls and trade shows. The environments in which these displays are located are complex, involving numerous users, making unlocking solely based on facial images inaccurate.

[0062] This application provides a face unlocking method, apparatus, and device, which aims to solve the above-mentioned technical problems of the prior art.

[0063] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0064] Figure 1 This is a flowchart illustrating a face unlocking method provided in an embodiment of this application, as shown below. Figure 1 As shown, the method includes:

[0065] S101. Obtain N first images of the user to be identified from N first image acquisition devices respectively, wherein each first image is acquired by each image acquisition device, the N first image acquisition devices are located at different first preset positions, and the first image is a face image of the user to be identified; and obtain a user dynamic image of the user to be identified from a second image acquisition device, wherein the second image acquisition device is located at a second preset position, and the user dynamic image is a body behavior image of the user to be identified; N is a positive integer greater than 1.

[0066] For example, the executing entity of this embodiment can be an electronic device, a server, a terminal device, or other apparatus or device capable of executing this embodiment. This embodiment uses an electronic device as an example for description.

[0067] Based on the control device in the electronic device, the control device connects to multiple image acquisition devices located in different positions. Among them, multiple image acquisition devices acquire facial images of the user to be identified, and one device acquires dynamic body behavior images of the user to be identified. The control device can obtain the images of the user to be identified from all the image acquisition devices.

[0068] In one example, due to the large acquisition area, in order to improve the accuracy of recognition, it is necessary to control the device to connect multiple image acquisition devices. The specific orientation of the devices (facing the large screen) is as follows: upper left of the large screen (device LT), directly above (device T1 + device T2), upper right (device RT), left center (device LC), and right center (device RC). Devices LT, T1, RT, LC, and RC are used to acquire the facial images of authorized users, and device T2 is used to acquire dynamic image information to analyze the body behavior information of authorized users.

[0069] S102. If it is determined that the comparison between one of the N first images and the pre-stored image is successful, then the user dynamic image is compared with the pre-stored dynamic image; wherein, the pre-stored image is the pre-stored user's face image; the pre-stored dynamic image is the pre-stored user's body behavior image.

[0070] For example, a face image is extracted from multiple face images and compared with a pre-stored user face image. If the image comparison between the extracted face image and the pre-stored user face image is successful, the obtained body behavior image of the user to be identified is compared with the pre-stored user body image. If the image comparison between the extracted face image and the pre-stored user face image fails, another face image is extracted from the multiple face images and compared again until a face image is successfully compared.

[0071] In one example, from multiple face images acquired by the first devices LT, T1, RT, LC, and RC, one face image acquired by device LT is randomly extracted as image 1. Image 1 is compared with the face image of a pre-stored authorized user. If the comparison between image 1 and the pre-stored authorized user's face image is successful, then the body behavior image of the user to be identified acquired by the second device T2 is compared with the body image of the pre-stored authorized user. If the comparison between image 1 and the pre-stored authorized user's face image fails, then from the multiple face images acquired by T1, RT, LC, and RC, one face image acquired by device L1 is randomly extracted as image 2. Image 2 is compared with the face image of the pre-stored authorized user, and this process continues until a successful comparison is achieved.

[0072] S103. In response to a successful comparison between the user's dynamic image and the pre-stored dynamic image, the large visual screen connected to the control device is unlocked.

[0073] For example, after comparing the acquired image of the user's body behavior with a pre-stored image of the user's body, if the comparison is successful, the screen of the visualization screen connected to the control device can be unlocked. If the comparison fails, a new image of the face and body behavior to be identified is acquired from the image acquisition device, and the comparison is repeated until the comparison is successful, thus achieving the effect of unlocking the visualization screen based on face recognition.

[0074] In one example, if the body behavior image of the user to be identified, collected by the second device T2, is compared with the body image of a pre-stored authorized user, and the comparison is successful, the screen of the large visualization screen connected to the control device can be unlocked. If the comparison between the body behavior image and the pre-stored authorized user's body image fails, the face image is compared again. If the comparison of all face images fails, the image of the user to be identified is collected again from the first device LT, T1, RT, LC, RC and the second device T2, and the comparison is performed again.

[0075] This embodiment provides a face unlocking method, which acquires N first images of a user to be identified, each acquired by a first image acquisition device located at a different first preset position, and the first image being a face image of the user to be identified; and acquires a user dynamic image of the user to be identified, acquired by a second image acquisition device located at a second preset position, and the user dynamic image being a body behavior image of the user to be identified; N is a positive integer greater than 1; if a comparison between one of the N first images and a pre-stored image is successful, the user dynamic image is compared with the pre-stored dynamic image; the pre-stored image is a pre-stored face image of the user; the pre-stored dynamic image is a pre-stored body behavior image of the user; in response to a successful comparison between the user dynamic image and the pre-stored dynamic image, the visualization screen connected to the control device is unlocked. First, the control device connects to multiple image acquisition devices located in different positions. Multiple image acquisition devices acquire facial images of the user to be identified, while one device acquires dynamic body movement images of the user. The control device can obtain the acquired images of the user from all the image acquisition devices. It then extracts a facial image from the multiple facial images and compares it with pre-stored user facial images. If the comparison is successful, the acquired body movement image of the user to be identified is compared with the pre-stored body movement image. If the comparison fails, the system starts again from the previous image. Extracting another face image from multiple face images and comparing them again until one face image is successfully compared; comparing the acquired body behavior image of the user to be identified with the pre-stored body behavior image of the user, if the comparison is successful, the screen of the visualization screen connected to the control device can be unlocked; if the comparison fails, new face image and body behavior image to be identified are acquired from the image acquisition device and compared again until the comparison is successful, thus achieving the effect of unlocking the visualization screen based on face recognition.

[0076] Figure 2 A flowchart illustrating another face unlocking method provided in this application embodiment is shown below. Figure 2 As shown, the method includes:

[0077] S201. Determine that all N first image acquisition devices and second image acquisition devices are in normal working condition.

[0078] For example, due to the large acquisition area, multiple image acquisition devices are needed to improve the accuracy of recognition, and it must be ensured that all devices are powered on and properly connected.

[0079] In one example, due to the large acquisition area, multiple image acquisition devices are needed to improve recognition accuracy. It is essential to ensure that all these devices are powered on and connected correctly. Specifically, the device positions (facing the large screen) are: top left (device LT), directly above (device T1 + device T2), top right (device RT), center left (device LC), and center right (device RC). Otherwise, the face recognition request will not be initiated. For example, if any of the multiple devices is not properly connected, the large screen will display the message "Device not properly connected, face unlock cannot be enabled!".

[0080] S202. In response to the face unlock request, the step of acquiring N first images of the user to be identified, acquired by N first image acquisition devices respectively, is performed; wherein, the face unlock request is used to instruct face unlock to be performed.

[0081] For example, the user is prompted to confirm whether they need to perform facial recognition to unlock the screen of the visualization screen. If the user confirms that they need to initiate the facial recognition request, multiple image acquisition devices are controlled to simultaneously acquire images of the user to be identified.

[0082] In one example, if it is determined that a face recognition request is enabled, control devices LT, T1, RT, LC, and RC are used to collect the face image of the authorized user, and control device T2 is used to collect dynamic image information to analyze the body behavior information of the authorized user. If it is determined that a face recognition request is not enabled, the large screen will display "Face unlock not enabled!", and other unlocking methods will be used or the user can directly enter the large screen without unlocking.

[0083] S203. Obtain N first images of the user to be identified from N first image acquisition devices respectively, wherein each first image is acquired by each image acquisition device, the N first image acquisition devices are located at different first preset positions, and the first image is a face image of the user to be identified; and obtain a user dynamic image of the user to be identified from a second image acquisition device, wherein the second image acquisition device is located at a second preset position, and the user dynamic image is a body behavior image of the user to be identified; N is a positive integer greater than 1.

[0084] For example, this step can be referred to step S101, and will not be described again.

[0085] S204. Extract first facial information from the i-th first image; wherein, the first facial information represents the light intensity information of the environment in which the user to be identified is located; i is a positive integer greater than or equal to 1 and less than or equal to N.

[0086] For example, based on the control device, the i-th face image, i.e. the i-th first image, is extracted from multiple face images. For the i-th first image, the light intensity information of the environment in which the user is located, i.e. the first facial information, is extracted from the face image.

[0087] In one example, based on the control device, the face image 1 acquired by LT is extracted from multiple face images obtained from devices LT, T1, RT, LC, and RC, i.e., the i-th first image. For the i-th first image, the light intensity information of the environment in which the user is located corresponding to face image 1 is extracted from face image 1.

[0088] S205. Based on the first facial information and the first pre-stored facial information, adjust the i-th first image to obtain the second image corresponding to the i-th first image; wherein, the first pre-stored facial information represents the pre-stored light intensity information of the user's environment.

[0089] For example, the light intensity information of the user's environment is obtained, and then the pre-stored light intensity information of the user's environment is obtained. The light intensity information corresponding to the i-th first image is adjusted with reference to the pre-stored light intensity information of the user's environment until it is consistent with the pre-stored light intensity information of the user's environment, so as to obtain the adjusted face image of the user to be identified.

[0090] In one example, a face image 1 is obtained from any device LT in the first device. The ambient light intensity in the face recognition information is adjusted. Based on the pre-stored ambient light intensity, it is determined whether the light is too strong or too dark. The ambient light intensity of the face image is automatically adjusted to obtain image 2.

[0091] S206. Compare the second image corresponding to the i-th first image with the pre-stored image to obtain a first matching value; wherein, the first matching value represents the degree of matching between the second image and the pre-stored image.

[0092] For example, based on an electronic device, the adjusted face image of the user to be identified is compared with a pre-stored face image of the user to obtain a matching value that can characterize the degree of matching between the two images.

[0093] S207. If the first matching value is greater than the first preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful.

[0094] For example, the matching value obtained by comparing the adjusted face image of the user to be identified with the pre-stored image is obtained, namely the first matching value. The matching value is compared with a preset threshold. If the matching value is greater than the preset threshold, it is determined that the comparison between the adjusted face image of the user to be identified and the pre-stored image is successful.

[0095] In one example, the matching value obtained by comparing the adjusted face image of the user to be identified with the pre-stored image is obtained, which is the first matching value. This matching value is compared with the preset 90%. If the matching value is greater than 90%, it is determined that the comparison between the adjusted face image of the user to be identified and the pre-stored image is successful. Based on the successfully matched user, the comparison continues.

[0096] After step S207, step S209 is executed.

[0097] S208. If the first matching value is less than or equal to the first preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed.

[0098] For example, the matching value obtained by comparing the adjusted face image of the user to be identified with the pre-stored image is obtained, namely the first matching value. The matching value is compared with a preset threshold. If the matching value is less than or equal to the preset threshold, it is determined that the comparison between the adjusted face image of the user to be identified and the pre-stored image has failed. Then, the (i+1)th face image is re-acquired, the light intensity information is readjusted, and the comparison continues until a face image is successfully compared.

[0099] In one example, the matching value obtained by comparing the adjusted face image of the user to be identified with the pre-stored image is obtained, which is the first matching value. This matching value is compared with the preset 90%. If the matching value is less than or equal to 90%, it is determined that the comparison between the adjusted face image of the user to be identified and the pre-stored image has failed. The face image of the adjusted user to be identified corresponds to image 1 collected by device T1. Then, T1 is removed from T1, RT, LC, and RC. From the remaining face images collected by devices RT, LC, and RC, one face image collected by device RT is randomly extracted as image 2. The light intensity information of image 2 is adjusted to obtain image 3. Image 3 is compared with the face image of the pre-stored authorized user until the comparison is successful.

[0100] After step S208, step S210 is executed.

[0101] S209. If it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful, then the user dynamic image is compared with the pre-stored dynamic image.

[0102] In one example, before comparing the user's animated image with a pre-stored animated image, step S209 includes the following steps:

[0103] The first step of step S209 is to extract second facial information and third facial information from the second image corresponding to the i-th first image; wherein, the second facial information represents the facial feature information of the user to be identified; and the third facial information represents the micro-expression information of the user to be identified.

[0104] In the second step of step S209, if it is determined that the comparison between the second facial information and the second pre-stored facial information is successful, and the comparison between the third facial information and the third pre-stored facial information is successful, then the step of comparing the user's dynamic image with the pre-stored dynamic image is executed; wherein, the second pre-stored facial information is the pre-stored facial feature information of the user; and the third pre-stored facial information is the pre-stored micro-expression information of the user.

[0105] In one example, before the second step of step S209, the following is included:

[0106] Step 1: Compare the second facial information with the second pre-stored facial information to obtain the second matching value; wherein, the second matching value represents the degree of matching between the second facial information and the second pre-stored facial information.

[0107] Step 2: If the second matching value is greater than the second preset threshold, then the comparison between the second facial information and the second pre-stored facial information is confirmed to be successful.

[0108] Step 3: If the second matching value is less than or equal to the second preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed.

[0109] In one example, prior to the second step of step S209, the following is also included:

[0110] Step 1: Compare the third facial information with the third pre-stored facial information to obtain the third matching value; whereby the third matching value represents the degree of matching between the third facial information and the third pre-stored facial information.

[0111] Step 2: If the third matching value is greater than the third preset threshold, then the comparison between the third facial information and the third pre-stored facial information is confirmed to be successful.

[0112] Step 3: If the third matching value is less than or equal to the third preset threshold, then the comparison between the second image corresponding to the i-th first image and the pre-stored image is determined to have failed.

[0113] For example, in order to improve the accuracy of face unlock, after it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful, the facial feature information and micro-expression information of the user to be identified are extracted from the second image corresponding to the i-th first image.

[0114] The facial feature information of the user to be identified is compared with the pre-stored facial feature information of the user to obtain the matching degree between the second facial information and the second pre-stored facial information, i.e., the corresponding second matching value. The matching value is compared with a preset threshold. If the matching value is greater than the preset threshold, it is determined that the facial feature information of the user to be identified is successfully matched with the pre-stored facial feature information of the user. If the matching value is less than or equal to the preset threshold, it is determined that the facial feature information of the user to be identified is unmatched with the pre-stored facial feature information of the user. It is necessary to re-acquire the (i+1)th face image, adjust the light intensity information, and then compare the facial feature information corresponding to the adjusted (i+1)th face image with the pre-stored facial feature information of the user again until the matching is successful.

[0115] Furthermore, after the facial feature information of the user to be identified is successfully compared with the pre-stored facial feature information of the user, the micro-expression information of the user to be identified is compared with the pre-stored micro-expression information of the user to obtain the matching degree between the micro-expression information of the user to be identified and the pre-stored micro-expression information, i.e., the third matching value. This matching value is compared with a preset threshold. If the matching value is greater than the preset threshold, it is determined that the micro-expression information of the user to be identified and the pre-stored micro-expression information of the user are successfully matched; if the matching value is less than or equal to the preset threshold, it is determined that the micro-expression information of the user to be identified and the pre-stored micro-expression information of the user are unmatched. It is necessary to re-acquire the (i+1)th face image, adjust the light intensity information, and then compare the micro-expression information corresponding to the adjusted (i+1)th face image with the pre-stored micro-expression information of the user again until the matching is successful.

[0116] Once it is confirmed that the facial features of the user to be identified are successfully matched with the pre-stored facial features of the user, and the micro-expression information of the user to be identified is successfully matched with the pre-stored micro-expression information of the user, the user's dynamic image and the pre-stored dynamic image are obtained and compared.

[0117] In one example, based on the control device, the face image 1 acquired by LT is extracted from multiple face images acquired by devices LT, T1, RT, LC, and RC. The ambient light intensity of the face image is automatically adjusted to obtain image 2. Facial feature information is extracted from image 2 and compared with the pre-stored facial feature information of the user to obtain a matching degree 1. If the matching degree 1 is greater than 95%, the comparison is successful, and the comparison continues based on the successfully matched user. If the matching degree 2 is less than or equal to 95%, then any face image acquired by device RT is randomly extracted from the multiple face images acquired by T1, RT, LC, and RC to obtain image 3. The light intensity information of image 3 is adjusted to obtain image 4. The facial feature information in image 4 is compared with the pre-stored facial feature information of the user until a successful comparison is obtained.

[0118] After the facial feature information extracted from image 2 is successfully compared with the pre-stored facial feature information of the user, micro-expression information is extracted from image 2 and compared with the pre-stored micro-expression information of the user to obtain a matching degree 2. If the matching degree 2 is greater than 90%, the comparison is successful, and the comparison continues based on the successfully matched user. If the matching degree 2 is less than or equal to 90%, then an image of the face captured by device RT is randomly extracted from multiple face images captured by T1, RT, LC, and RC, which is image 3. After adjusting the light intensity information of image 3, it becomes image 4. The micro-expression information in image 4 is compared with the pre-stored micro-expression information of the user until the comparison is successful.

[0119] Once the facial feature information extracted from image 2 is successfully compared with the pre-stored facial feature information of the user, and the micro-expression information in image 2 is successfully compared with the pre-stored micro-expression information of the user, the dynamic body behavior image captured by device T2 is compared with the body behavior image of the pre-stored authorized user.

[0120] S210. If it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image fails, then the value of i is incremented by 1.

[0121] For example, after step S208, if the image comparison between the face image and the pre-stored user face image fails, another face image is extracted from multiple face images and compared again until a face image is successfully compared.

[0122] In one example, the first face image is randomly extracted from multiple face images acquired by the first device LT, T1, RT, LC, RC, and is designated as image 1. Image 1 is compared with the face images of pre-stored authorized users. If the image comparison between the face image and the pre-stored face images of users fails, the second face image is extracted from the multiple face images again, and the comparison is repeated until a face image is successfully compared.

[0123] S211. Compare the user's dynamic image with the pre-stored dynamic image to obtain a fourth matching value; wherein, the fourth matching value represents the degree of matching between the user's dynamic image and the pre-stored dynamic image.

[0124] For example, the device acquires images of the user's body behavior collected by the device and images of the user's body behavior that are stored in the database. The images of the user's body behavior collected by the device are compared with the images of the user's body behavior that are stored in the database to obtain the degree of matching between the images of the user's body behavior collected by the device and the images of the user's body behavior that are stored in the database, i.e., the fourth matching value.

[0125] S212. If the fourth matching value is greater than the fourth preset threshold, then the comparison between the user's dynamic image and the pre-stored dynamic image is determined to be successful.

[0126] For example, the matching degree between the image of the user's body behavior to be identified and the pre-stored image of the user's body behavior, i.e., the fourth matching value, is compared with the preset matching degree. If the matching degree is greater than the preset matching degree, it is determined that the comparison between the image of the user's body behavior to be identified and the pre-stored image of the user's body behavior is successful, i.e., the comparison between the user's dynamic image and the pre-stored dynamic image is successful.

[0127] In one example, the matching degree between the body behavior image of the user to be identified and the pre-stored body behavior images of the user, i.e., the fourth matching value, is compared with a preset 90%. If the matching degree is greater than the preset 90%, it is determined that the comparison between the body behavior image of the user to be identified and the pre-stored body behavior images of the user is successful, that is, it is determined that the comparison between the user's dynamic image and the pre-stored dynamic image is successful. The face image, facial feature information, and micro-expression information corresponding to this successful comparison are added to the storage unit corresponding to the pre-stored authorized user, and the image acquisition device stops collecting information.

[0128] After step S212, step S214 is executed.

[0129] S213. If the fourth matching value is less than or equal to the fourth preset threshold, it is determined that the comparison between the user's dynamic image and the pre-stored dynamic image has failed, and the step of acquiring the N first images of the user to be identified acquired by the N first image acquisition devices is executed again.

[0130] For example, the matching degree between the body behavior image of the user to be identified and the pre-stored body behavior image of the user, i.e., the fourth matching value, is compared with the preset matching degree. If the matching degree is less than or equal to the preset matching degree, it is determined that the comparison between the body behavior image of the user to be identified and the pre-stored body behavior image of the user has failed, i.e., the comparison between the user dynamic image and the pre-stored dynamic image has failed. Then, new face image and body behavior image to be identified are obtained from the image acquisition device again, and the comparison is repeated until the comparison is successful, so as to achieve the effect of unlocking the visual large screen based on face recognition.

[0131] S214. In response to a successful comparison between the user's dynamic image and a pre-stored dynamic image, the large visual screen connected to the control device is unlocked.

[0132] For example, after step S212, the acquired body behavior image of the user to be identified is compared with the pre-stored body image of the user. If it is determined that the comparison between the acquired body behavior image of the user to be identified and the pre-stored body image of the user is successful, the screen of the visualization screen connected to the control device can be unlocked. If it is determined that the comparison between the acquired body behavior image of the user to be identified and the pre-stored body image of the user is unsuccessful, a new face image and body behavior image to be identified are acquired from the image acquisition device and compared again until the comparison is successful, thereby achieving the effect of unlocking the visualization screen based on face recognition.

[0133] In this embodiment, based on the above embodiments, first facial information is extracted from the i-th first image; the i-th first image is adjusted according to the first facial information and the first pre-stored facial information to obtain a second image corresponding to the i-th first image; the second image corresponding to the i-th first image is compared with the pre-stored image to obtain a first matching value; if the first matching value is greater than a first preset threshold, it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful; second facial information and third facial information are extracted from the second image corresponding to the i-th first image; wherein, the second facial information represents the facial feature information of the user to be identified; the third facial information represents the micro-expression information of the user to be identified; if it is determined that the comparison between the second facial information and the second pre-stored facial information is successful, and it is determined that the comparison between the third facial information and the third pre-stored facial information is successful, then the step of comparing the user's dynamic image with the pre-stored dynamic image is executed. Multiple image acquisition devices are used to collect images of the user to be identified, including facial images, multiple facial information and body behavior information. The acquired image information is compared with pre-stored information. Even in complex on-site environments, such as when there are many people and they are in motion, the face can be accurately identified to unlock the screen of the visualization screen, thus achieving the effect of unlocking the visualization screen based on face recognition.

[0134] Figure 3 This is a schematic diagram of the structure of a face unlocking device provided in an embodiment of this application, as shown below. Figure 3 As shown, the device 300 includes:

[0135] The acquisition unit 301 is used to acquire N first images of the user to be identified, each acquired by one of the N first image acquisition devices, wherein each first image is acquired by one of the N first image acquisition devices, the N first image acquisition devices are located at different first preset positions, and the first image is a face image of the user to be identified; and to acquire user dynamic images of the user to be identified, acquired by a second image acquisition device, wherein the second image acquisition device is located at a second preset position, and the user dynamic images are images of the body behavior of the user to be identified; N is a positive integer greater than 1.

[0136] The first determining unit 302 is used to compare the user's dynamic image with the pre-stored dynamic image if a comparison between one of the N first images and the pre-stored image is successful; wherein the pre-stored image is a pre-stored image of the user's face; and the pre-stored dynamic image is a pre-stored image of the user's body behavior.

[0137] The unlocking unit 303 is used to unlock the large visual screen connected to the control device in response to a successful comparison between the user's dynamic image and a pre-stored dynamic image.

[0138] The apparatus in this embodiment can execute the technical solutions in the above method. Its specific implementation process and technical principles are the same, and will not be repeated here.

[0139] Figure 4 This is a schematic diagram of another face unlocking device provided in an embodiment of this application, as shown below. Figure 4 As shown, the device 400 includes:

[0140] The acquisition unit 401 is used to acquire N first images of the user to be identified, each acquired by one of the N first image acquisition devices, wherein each first image is acquired by one of the N first image acquisition devices, the N first image acquisition devices are located at different first preset positions, and the first image is a face image of the user to be identified; and to acquire a user dynamic image of the user to be identified, acquired by a second image acquisition device, wherein the second image acquisition device is located at a second preset position, and the user dynamic image is a body behavior image of the user to be identified; N is a positive integer greater than 1.

[0141] The first determining unit 402 is used to compare the user's dynamic image with the pre-stored dynamic image if a comparison between one of the N first images and the pre-stored image is successful; wherein the pre-stored image is a pre-stored image of the user's face; and the pre-stored dynamic image is a pre-stored image of the user's body behavior.

[0142] The unlocking unit 403 is used to unlock the large visual screen connected to the control device in response to a successful comparison between the user's dynamic image and a pre-stored dynamic image.

[0143] In one example, the first determining unit 402 includes:

[0144] Repeat the steps from the first extraction module 4021 to the second determination module 4024 until a comparison between one of the N first images and the pre-stored image is successful:

[0145] The first extraction module 4021 is used to extract first facial information from the i-th first image; wherein the first facial information represents the light intensity information of the environment in which the user to be identified is located; i is a positive integer greater than or equal to 1 and less than or equal to N.

[0146] The adjustment module 4022 is used to adjust the i-th first image according to the first facial information and the first pre-stored facial information to obtain the second image corresponding to the i-th first image; wherein, the first pre-stored facial information represents the pre-stored light intensity information of the user's environment.

[0147] The first determining module 4023 is used to compare the user dynamic image with the pre-stored dynamic image if the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful.

[0148] The second determining module 4024 is used to determine that if the comparison between the second image corresponding to the i-th first image and the pre-stored image fails, the value of i is incremented by 1.

[0149] In one example, device 400 also includes:

[0150] The comparison module 4025 is used to compare the second image corresponding to the i-th first image with the pre-stored image to obtain a first matching value; wherein, the first matching value represents the degree of matching between the second image and the pre-stored image.

[0151] The third determining module 4026 is used to determine that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful if the first matching value is greater than the first preset threshold.

[0152] The fourth determining module 4027 is used to determine that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed if the first matching value is less than or equal to the first preset threshold.

[0153] In one example, before the first determining module 4023 compares the user's motion image with a pre-stored motion image, it includes:

[0154] The second extraction module 4028 is used to extract second facial information and third facial information from the second image corresponding to the i-th first image; wherein, the second facial information represents the facial feature information of the user to be identified; and the third facial information represents the micro-expression information of the user to be identified.

[0155] The fifth determining module 4029 is used to perform the step of comparing the user's dynamic image with the pre-stored dynamic image if it is determined that the comparison between the second facial information and the second pre-stored facial information is successful, and the comparison between the third facial information and the third pre-stored facial information is successful; wherein, the second pre-stored facial information is the pre-stored facial feature information of the user; and the third pre-stored facial information is the pre-stored micro-expression information of the user.

[0156] In one example, device 400 also includes:

[0157] The first comparison module 4030 is used to compare the second facial information with the second pre-stored facial information to obtain a second matching value; wherein, the second matching value represents the degree of matching between the second facial information and the second pre-stored facial information.

[0158] The sixth determining module 4031 is used to determine that the comparison between the second facial information and the second pre-stored facial information is successful if the second matching value is greater than the second preset threshold.

[0159] The seventh determining module 4032 is used to determine that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed if the second matching value is less than or equal to the second preset threshold.

[0160] In one example, device 400 includes:

[0161] The second comparison module 4033 is used to compare the third facial information with the third pre-stored facial information to obtain a third matching value; wherein, the third matching value represents the degree of matching between the third facial information and the third pre-stored facial information.

[0162] The eighth determining module 4034 is used to determine that the comparison between the third facial information and the third pre-stored facial information is successful if the third matching value is greater than the third preset threshold.

[0163] The ninth determining module 4035 is used to determine that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed if the third matching value is less than or equal to the third preset threshold.

[0164] In one example, device 400 also includes:

[0165] The comparison unit 404 is used to compare the user's dynamic image with the pre-stored dynamic image to obtain a fourth matching value; wherein, the fourth matching value represents the degree of matching between the user's dynamic image and the pre-stored dynamic image.

[0166] The second determining unit 405 is used to determine that the comparison between the user's dynamic image and the pre-stored dynamic image is successful if the fourth matching value is greater than the fourth preset threshold.

[0167] The third determining unit 406 is used to determine that the comparison between the user's dynamic image and the pre-stored dynamic image has failed if the fourth matching value is less than or equal to the fourth preset threshold, and to execute the step of acquiring the N first images of the user to be identified acquired by the N first image acquisition devices respectively.

[0168] In one example, device 400 also includes:

[0169] The response unit 407 is configured to, in response to a face unlock request, perform the step of acquiring N first images of the user to be identified, each acquired by one of the N first image acquisition devices; wherein the face unlock request is used to instruct face unlock to be performed.

[0170] In one example, device 400 also includes:

[0171] The fourth determining unit 408 is used to determine that if all N first image acquisition devices and the second image acquisition device are in normal working condition, then execute the step of acquiring N first images of the user to be identified acquired by the N first image acquisition devices respectively.

[0172] The apparatus in this embodiment can execute the technical solutions in the above method. Its specific implementation process and technical principles are the same, and will not be repeated here.

[0173] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 5 As shown, the electronic device 50 includes: a memory 51 and a processor 52; the memory 51 is a memory for storing executable instructions of the processor 52.

[0174] The processor 52 is configured to perform the methods provided in the above embodiments.

[0175] The terminal device also includes a receiver 53 and a transmitter 54. The receiver 53 is used to receive instructions and data sent by other devices, and the transmitter 54 is used to send instructions and data to external devices.

[0176] Figure 6This is a block diagram illustrating an electronic device according to an exemplary embodiment. The device may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc.

[0177] The device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0178] Processing component 802 typically controls the overall operation of device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0179] Memory 804 is configured to store various types of data to support the operation of device 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0180] Power supply component 806 provides power to various components of device 800. Power supply component 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to device 800.

[0181] Multimedia component 808 includes a screen that provides an output interface between device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0182] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0183] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0184] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of device 800. For example, sensor assembly 814 may detect the on / off state of device 800, the relative positioning of components such as the display and keypad of device 800, changes in the position of device 800 or a component of device 800, the presence or absence of user contact with device 800, the orientation or acceleration / deceleration of device 800, and temperature changes of device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0185] Communication component 816 is configured to facilitate wired or wireless communication between device 800 and other devices. Device 800 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0186] In an exemplary embodiment, the apparatus 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0187] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of the device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0188] This application also provides a non-transitory computer-readable storage medium, which, when the instructions in the storage medium are executed by the processor of an electronic device, enables the electronic device to perform the above-described method.

[0189] According to an embodiment of this application, this application also provides a computer program product, which includes: a computer program stored in a readable storage medium, at least one processor of an electronic device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to cause the electronic device to perform the solution provided in any of the above embodiments.

[0190] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0191] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A face unlocking method, characterized in that, The method is applied to a control device, and the method includes: The system acquires N first images of the user to be identified, each acquired by a different first image acquisition device. Each first image is acquired by a different first preset position, and the first image is a facial image of the user to be identified. The system also acquires a user dynamic image of the user to be identified, acquired by a second image acquisition device, located at a second preset position. The user dynamic image is a body movement image of the user to be identified. N is a positive integer greater than 1. Repeat the following steps until one of the N first images is successfully compared with the pre-stored image: First facial information is extracted from the i-th first image; wherein the first facial information represents the light intensity information of the environment in which the user to be identified is located; i is a positive integer greater than or equal to 1 and less than or equal to N; Based on the first facial information and the first pre-stored facial information, the i-th first image is adjusted to obtain the second image corresponding to the i-th first image; wherein, the first pre-stored facial information represents the pre-stored light intensity information of the user's environment; Second facial information and third facial information are extracted from the second image corresponding to the i-th first image; wherein, the second facial information represents the facial feature information of the user to be identified; and the third facial information represents the micro-expression information of the user to be identified. If it is determined that the comparison between the second facial information and the second pre-stored facial information is successful, and the comparison between the third facial information and the third pre-stored facial information is successful, then the step of comparing the user's dynamic image with the pre-stored dynamic image is executed; wherein, the second pre-stored facial information is the pre-stored facial feature information of the user; the third pre-stored facial information is the pre-stored micro-expression information of the user; wherein, the pre-stored image is the pre-stored face image of the user; and the pre-stored dynamic image is the pre-stored image of the user's body behavior. If the comparison between the user's dynamic image and the pre-stored dynamic image is successful, the visualization screen connected to the control device will be unlocked.

2. The method according to claim 1, characterized in that, The method further includes: If it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful, then the user dynamic image is compared with the pre-stored dynamic image; If it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image fails, then the value of i is incremented by 1.

3. The method according to claim 2, characterized in that, The method further includes: The second image corresponding to the i-th first image is compared with the pre-stored image to obtain a first matching value; wherein, the first matching value represents the degree of matching between the second image and the pre-stored image; If the first matching value is greater than the first preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful; If the first matching value is less than or equal to the first preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed.

4. The method according to claim 2, characterized in that, The method further includes: The second facial information is compared with the second pre-stored facial information to obtain a second matching value; wherein, the second matching value represents the degree of matching between the second facial information and the second pre-stored facial information; If the second matching value is greater than the second preset threshold, then the comparison between the second facial information and the second pre-stored facial information is determined to be successful. If the second matching value is less than or equal to the second preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed.

5. The method according to claim 2, characterized in that, The method includes: The third facial information is compared with the third pre-stored facial information to obtain a third matching value; wherein, the third matching value represents the degree of matching between the third facial information and the third pre-stored facial information; If the third matching value is greater than the third preset threshold, then the comparison between the third facial information and the third pre-stored facial information is determined to be successful; If the third matching value is less than or equal to the third preset threshold, then it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed.

6. The method according to claim 1, characterized in that, The method further includes: The user's dynamic image is compared with the pre-stored dynamic image to obtain a fourth matching value; wherein, the fourth matching value represents the degree of matching between the user's dynamic image and the pre-stored dynamic image; If the fourth matching value is greater than the fourth preset threshold, then the comparison between the user's dynamic image and the pre-stored dynamic image is determined to be successful. If the fourth matching value is less than or equal to the fourth preset threshold, it is determined that the comparison between the user dynamic image and the pre-stored dynamic image has failed, and the step of acquiring N first images of the user to be identified acquired by N first image acquisition devices is executed again.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: In response to a face unlock request, the step of acquiring N first images of the user to be identified, each acquired by a first image acquisition device, is performed; wherein the face unlock request is used to instruct face unlock to be performed.

8. The method according to any one of claims 1-6, characterized in that, The method further includes: If it is determined that the N first image acquisition devices and the second image acquisition device are all in normal working condition, then the step of acquiring the N first images of the user to be identified acquired by the N first image acquisition devices is executed.

9. A face unlocking device, characterized in that, The device is used in a control device, and the device includes: The acquisition unit is configured to acquire N first images of the user to be identified, each acquired by a first image acquisition device, wherein each first image is acquired by a single image acquisition device, the N first image acquisition devices are located at different first preset positions, and the first image is a facial image of the user to be identified; and to acquire a user dynamic image of the user to be identified, acquired by a second image acquisition device, wherein the second image acquisition device is located at a second preset position, and the user dynamic image is a body behavior image of the user to be identified; N is a positive integer greater than 1; The first determining unit is configured to compare the user dynamic image with the pre-stored dynamic image if a successful comparison is found between one of the N first images and a pre-stored image; wherein the pre-stored image is a pre-stored image of the user's face; and the pre-stored dynamic image is a pre-stored image of the user's body movements. The unlocking unit is used to unlock the large visual screen connected to the control device in response to a successful comparison between the user's dynamic image and the pre-stored dynamic image. The first determining unit includes: Repeat the steps from the first extraction module to the second determination module until a comparison between one of the N first images and a pre-stored image is successful: The first extraction module is used to extract first facial information from the i-th first image; wherein the first facial information represents the light intensity information of the environment in which the user to be identified is located; i is a positive integer greater than or equal to 1 and less than or equal to N; The adjustment module is used to adjust the i-th first image according to the first facial information and the first pre-stored facial information to obtain the second image corresponding to the i-th first image; wherein, the first pre-stored facial information represents the pre-stored light intensity information of the user's environment; Before the first determining module compares the user's dynamic image with the pre-stored dynamic image, the process includes: The second extraction module is used to extract second facial information and third facial information from the second image corresponding to the i-th first image; wherein, the second facial information represents the facial feature information of the user to be identified; and the third facial information represents the micro-expression information of the user to be identified. The fifth determining module is used to perform the step of comparing the user's dynamic image with the pre-stored dynamic image if it is determined that the comparison between the second facial information and the second pre-stored facial information is successful, and the comparison between the third facial information and the third pre-stored facial information is successful; wherein, the second pre-stored facial information is the pre-stored facial feature information of the user; and the third pre-stored facial information is the pre-stored micro-expression information of the user.

10. The apparatus according to claim 9, characterized in that, The first determining unit further includes: The first determining module is used to compare the user dynamic image with the pre-stored dynamic image if it is determined that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful. The second determining module is used to determine that if the comparison between the second image corresponding to the i-th first image and the pre-stored image fails, the value of i is incremented by 1.

11. The apparatus according to claim 10, characterized in that, The device further includes: The comparison module is used to compare the second image corresponding to the i-th first image with the pre-stored image to obtain a first matching value; wherein, the first matching value represents the degree of matching between the second image and the pre-stored image; The third determining module is used to determine that the comparison between the second image corresponding to the i-th first image and the pre-stored image is successful if the first matching value is greater than the first preset threshold. The fourth determining module is used to determine that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed if the first matching value is less than or equal to the first preset threshold.

12. The apparatus according to claim 10, characterized in that, The device further includes: The first comparison module is used to compare the second facial information with the second pre-stored facial information to obtain a second matching value; wherein, the second matching value represents the degree of matching between the second facial information and the second pre-stored facial information; The sixth determining module is used to determine that the comparison between the second facial information and the second pre-stored facial information is successful if the second matching value is greater than the second preset threshold. The seventh determining module is used to determine that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed if the second matching value is less than or equal to the second preset threshold.

13. The apparatus according to claim 10, characterized in that, The device includes: The second comparison module is used to compare the third facial information with the third pre-stored facial information to obtain a third matching value; wherein, the third matching value represents the degree of matching between the third facial information and the third pre-stored facial information; The eighth determining module is used to determine that the comparison between the third facial information and the third pre-stored facial information is successful if the third matching value is greater than the third preset threshold. The ninth determining module is used to determine that the comparison between the second image corresponding to the i-th first image and the pre-stored image has failed if the third matching value is less than or equal to the third preset threshold.

14. The apparatus according to claim 9, characterized in that, The device further includes: The comparison unit is used to compare the user dynamic image with the pre-stored dynamic image to obtain a fourth matching value; wherein, the fourth matching value represents the degree of matching between the user dynamic image and the pre-stored dynamic image; The second determining unit is used to determine that the comparison between the user dynamic image and the pre-stored dynamic image is successful if the fourth matching value is greater than the fourth preset threshold. The third determining unit is used to determine that the comparison between the user dynamic image and the pre-stored dynamic image has failed if the fourth matching value is less than or equal to the fourth preset threshold, and to execute the step of acquiring N first images of the user to be identified acquired by N first image acquisition devices respectively.

15. The apparatus according to any one of claims 9-14, characterized in that, The device further includes: A response unit is configured to, in response to a face unlock request, execute the step of acquiring N first images of the user to be identified, each acquired by one of the N first image acquisition devices; wherein the face unlock request is used to instruct face unlock to be performed.

16. The apparatus according to any one of claims 9-14, characterized in that, The device further includes: The fourth determining unit is used to determine that if the N first image acquisition devices and the second image acquisition device are all in normal working condition, then execute the step of acquiring the N first images of the user to be identified acquired by the N first image acquisition devices respectively.

17. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-8.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-8.

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