Method and device for identifying smart door lock, electronic device and storage medium

Abstract

The present disclosure discloses a method and device for identifying a smart door lock, an electronic device and a storage medium, and relates to the technical field of electronic devices, including: obtaining a two-dimensional face image based on a camera and identifying it to obtain a first similarity; identifying a three-dimensional face image to obtain a second similarity; if the second similarity is greater than or equal to a lower limit value of the three-dimensional face image similarity and less than an upper limit value of the three-dimensional face image similarity, then judging whether the first similarity is greater than a first two-dimensional face image similarity threshold; if the first similarity is greater than the first two-dimensional face image similarity threshold, then unlocking is performed. Compared with the related art, when the second similarity is within the range of the lower limit value of the three-dimensional face image similarity and the upper limit value of the three-dimensional face image similarity, it is supplemented based on the first similarity, so that when the accuracy of the three-dimensional face image recognition is insufficient, unlocking is performed based on the first similarity, thereby improving the adaptability of the three-dimensional face recognition to the external environment.

Description

Technical Field

[0001] The present disclosure relates to the technical field of electronic devices, and in particular to a method and device for identifying a smart door lock, an electronic device, and a storage medium. Background Art

[0002] The three-dimensional face recognition involved in the current smart door locks only relies on the three-dimensional face image of the user for recognition. Therefore, the recognition process of the three-dimensional face recognition is easily affected by external conditions, resulting in recognition failure. For example, when using three-dimensional face recognition to open the door, if the light is poor, the effect of the smart door lock in recognizing the three-dimensional face image will be reduced to a certain extent, resulting in unlocking failure. Summary of the invention

[0003] The present disclosure provides a method and device for identifying a smart door lock, an electronic device and a storage medium, and aims to solve the problem in the related art that the three-dimensional face recognition involved in the smart door lock is easily affected by external conditions, resulting in recognition failure.

[0004] According to a first aspect of the present disclosure, a method for identifying a smart door lock is provided, comprising:

[0005] Acquire a two-dimensional face image based on a camera, and recognize the two-dimensional face image to obtain a first similarity;

[0006] In response to a request for identifying a three-dimensional face image, identifying the three-dimensional face image to obtain a second similarity;

[0007] If the second similarity is greater than or equal to a lower limit of the three-dimensional face image similarity and less than an upper limit of the three-dimensional face image similarity, determining whether the first similarity is greater than a first two-dimensional face image similarity threshold;

[0008] If the first similarity is greater than the first two-dimensional face image similarity threshold, unlocking is performed.

[0009] Optionally, after identifying the three-dimensional face image and obtaining the second similarity, the method further includes:

[0010] If the second similarity is less than the lower limit of the three-dimensional face image similarity, unlocking is not performed;

[0011] If the second similarity is greater than or equal to the upper limit of the similarity of the three-dimensional face image, unlocking is performed.

[0012] Optionally, after identifying the two-dimensional face image and obtaining the first similarity, the method further includes:

[0013] In response to a request for identification of a finger vein image, identifying the finger vein image to obtain a third similarity;

[0014] If the third similarity is greater than or equal to the lower limit of the finger vein image similarity and less than the upper limit of the finger vein image similarity, determining whether the first similarity is greater than the first two-dimensional face image similarity threshold;

[0015] If the first similarity is greater than the first two-dimensional face image similarity threshold, unlocking is performed.

[0016] Optionally, after identifying the finger vein image and obtaining the third similarity, the method further includes:

[0017] If the third similarity is less than the finger vein image similarity lower limit, unlocking is not performed;

[0018] If the third similarity is greater than or equal to the finger vein image similarity upper limit value, unlocking is performed.

[0019] Optionally, the acquiring of a two-dimensional face image based on a camera includes:

[0020] Call the preset sensor to monitor whether the environment of the preset monitoring area has changed;

[0021] If it is determined that the environment of the preset monitoring area has changed, waking up the camera;

[0022] When it is determined that the camera detects a human-shaped image, the two-dimensional human face image is acquired.

[0023] Optionally, after waking up the camera, the method further includes:

[0024] When it is determined that the camera detects a non-human image, the camera is controlled to enter a dormant state.

[0025] Optionally, before recognizing the three-dimensional face image, the method further includes:

[0026] Determining whether the first similarity is greater than a second two-dimensional face similarity threshold;

[0027] The identifying of the three-dimensional face image comprises:

[0028] If the first similarity is greater than the second two-dimensional face similarity threshold, ultrasound is started, and the three-dimensional face image is collected based on the ultrasound.

[0029] According to a second aspect of the present disclosure, a device for identifying a smart door lock is provided, comprising:

[0030] A first recognition unit, configured to obtain a two-dimensional face image based on a camera, and recognize the two-dimensional face image to obtain a first similarity;

[0031] A second recognition unit, configured to recognize the three-dimensional face image in response to a recognition request of the three-dimensional face image, and obtain a second similarity;

[0032] A first judging unit, configured to judge whether the first similarity is greater than a first two-dimensional face image similarity threshold when the second similarity is greater than or equal to a three-dimensional face image similarity lower limit and less than a three-dimensional face image similarity upper limit;

[0033] The first execution unit executes unlocking when the first similarity is greater than the first two-dimensional face image similarity threshold.

[0034] Optionally, the first execution unit is further used for:

[0035] When the second similarity is less than the lower limit of the three-dimensional face image similarity, unlocking is not performed;

[0036] When the second similarity is greater than or equal to the upper limit of the similarity of the three-dimensional face image, unlocking is performed.

[0037] Optionally, the device further comprises:

[0038] a third recognition unit, configured to recognize the finger vein image in response to a recognition request of the finger vein image, and obtain a third similarity;

[0039] a second judgment unit, configured to judge whether the first similarity is greater than a first two-dimensional face image similarity threshold when the third similarity is greater than or equal to a finger vein image similarity lower limit and less than a finger vein image similarity upper limit;

[0040] The second execution unit is used to execute unlocking when the first similarity is greater than the first two-dimensional face image similarity threshold.

[0041] Optionally, the second execution unit is further used for:

[0042] When the third similarity is less than the finger vein image similarity lower limit, unlocking is not performed;

[0043] When the third similarity is greater than or equal to the finger vein image similarity upper limit value, unlocking is performed.

[0044] Optionally, the first identification unit includes:

[0045] A calling module is used to call a preset sensor to monitor whether the environment of a preset monitoring area has changed;

[0046] A wake-up module, used to wake up the camera when it is determined that the environment of the preset monitoring area has changed;

[0047] The acquisition module is used to acquire the two-dimensional human face image when it is determined that the camera detects a human image.

[0048] Optionally, the device further comprises:

[0049] The control unit is used to control the camera to enter a dormant state when it is determined that the camera detects a non-human image.

[0050] Optionally, the device further comprises:

[0051] A third judgment unit, used to judge whether the first similarity is greater than a second two-dimensional face similarity threshold;

[0052] The second identification unit is further used for:

[0053] When the first similarity is greater than the second two-dimensional face similarity threshold, ultrasound is started, and the three-dimensional face image is collected based on the ultrasound.

[0054] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0055] at least one processor; and

[0056] a memory communicatively connected to the at least one processor; wherein,

[0057] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0058] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0059] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0060] The present invention provides a method and device for identifying a smart door lock, an electronic device and a storage medium, and the main technical scheme includes: obtaining a two-dimensional face image based on a camera, and identifying the two-dimensional face image to obtain a first similarity; in response to a request for identifying a three-dimensional face image, identifying the three-dimensional face image to obtain a second similarity; if the second similarity is greater than or equal to a lower limit value of the three-dimensional face image similarity and less than an upper limit value of the three-dimensional face image similarity, determining whether the first similarity is greater than a first two-dimensional face image similarity threshold; if the first similarity is greater than the first two-dimensional face image similarity threshold, unlocking is performed. Compared with the related art, the second similarity is obtained based on the recognition of the three-dimensional face image. When the second similarity is within the interval between the lower limit value of the three-dimensional face image similarity and the upper limit value of the three-dimensional face image similarity, it is necessary to further verify the first similarity obtained based on the recognition of the two-dimensional face image. When the first similarity is greater than the first two-dimensional face image similarity threshold, the smart door lock executes unlocking. Through double verification, when the accuracy of the three-dimensional face image recognition is insufficient, the door can be unlocked by referring to the recognition result of the two-dimensional face image, which improves the adaptability of the three-dimensional face recognition to the external environment to a certain extent.

[0061] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0063] Figure 1 A flowchart of a method for identifying a smart door lock provided by an embodiment of the present disclosure;

[0064] Figure 2 A schematic diagram of the structure of a device for identifying a smart door lock provided in an embodiment of the present disclosure;

[0065] Figure 3 A schematic diagram of the structure of another device for identifying a smart door lock provided in an embodiment of the present disclosure;

[0066] Figure 4 A schematic block diagram of an exemplary electronic device 300 provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0067] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0068] The following describes the method and device for identifying a smart door lock, an electronic device, and a storage medium according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0069] Figure 1 A flowchart of a method for identifying a smart door lock provided in an embodiment of the present disclosure.

[0070] like Figure 1 As shown, the method comprises the following steps:

[0071] Step 101: Acquire a two-dimensional face image based on a camera, and recognize the two-dimensional face image to obtain a first similarity.

[0072] In some implementations of this embodiment, the camera may be a color camera, and the camera may be used to collect two-dimensional facial images. In order to more clearly explain the implementation process of the above step 101, an exemplary description is provided here, for example: the user approaches the camera and the camera collects the user's two-dimensional facial image, and then the two-dimensional facial image is compared with the two-dimensional facial image already entered in the database for similarity, that is, recognition is performed, and the degree of similarity between the two-dimensional facial image and the two-dimensional facial image in the database, that is, the first similarity, is obtained. It should be understood that the above exemplary description does not constitute a limitation on the similarity comparison method disclosed in the present disclosure.

[0073] Step 102: In response to a request for identifying a three-dimensional face image, identify the three-dimensional face image to obtain a second similarity.

[0074] In some possible implementations of this embodiment, when the user uses three-dimensional face recognition, the smart door lock responds to the request for three-dimensional face recognition, then collects the user's three-dimensional face image, and then compares the three-dimensional face image with the three-dimensional face image already entered into the database for similarity, i.e., performs recognition, and obtains the degree of similarity between the three-dimensional face image and the three-dimensional face image already entered into the database, i.e., the second similarity.

[0075] Step 103: determine whether the first similarity is greater than a first two-dimensional face image similarity threshold.

[0076] If the second similarity is greater than or equal to the lower limit of the three-dimensional face image similarity and less than the upper limit of the three-dimensional face image similarity, step 103 is executed.

[0077] As a refinement of the above step 103, in step 103, a judgment interval range of the second similarity is given, that is, the lower limit value of the three-dimensional face image similarity and the upper limit value of the three-dimensional face image similarity. It should be understood that the upper limit value of the three-dimensional face image similarity is greater than the lower limit value of the three-dimensional face image similarity, and the greater the second similarity, the more similar the three-dimensional face image recognized by the smart door lock is to the three-dimensional face image already entered in the database, that is, the heavier the weight of controlling the unlocking of the smart door lock. If the second similarity is in an intermediate range, that is, the second similarity is greater than or equal to the lower limit value of the three-dimensional face similarity and less than the upper limit value of the three-dimensional face image similarity, the weight ratio of executing unlocking and not unlocking will be similar. At this time, it is necessary to introduce the first similarity obtained by recognizing the two-dimensional face image to determine the weight relationship between unlocking and not unlocking, that is, it is necessary to determine whether the first similarity is greater than the first two-dimensional face image similarity threshold.

[0078] The values ​​involved in the above embodiments, such as the lower limit value of the three-dimensional face similarity, the upper limit value of the three-dimensional face similarity, and the first two-dimensional face image similarity threshold value, can be adjusted according to the actual implementation environment.

[0079] Step 104, unlocking is performed.

[0080] If the first similarity is greater than the first two-dimensional face image similarity threshold, step 104 is executed.

[0081] It is known in the detailed description of the above step 103 that the judgment of the first similarity is to further determine the weight relationship of the smart door lock executing unlocking or not unlocking. When the first similarity is greater than the first two-dimensional face image similarity threshold, it is determined that the weight of unlocking is greater than the weight of not unlocking. Therefore, when the smart door lock executes unlocking, it should be understood that the larger the value of the first similarity is, the higher the similarity between the two-dimensional face image of the user obtained based on the camera and the two-dimensional face image in the database is.

[0082] The present invention discloses a method for identifying a smart door lock, and its main technical solutions include: obtaining a two-dimensional face image based on a camera, and identifying the two-dimensional face image to obtain a first similarity; in response to a request for identifying a three-dimensional face image, identifying the three-dimensional face image to obtain a second similarity; if the second similarity is greater than or equal to a lower limit value of the three-dimensional face image similarity and less than an upper limit value of the three-dimensional face image similarity, determining whether the first similarity is greater than a first two-dimensional face image similarity threshold; if the first similarity is greater than the first two-dimensional face image similarity threshold, unlocking is performed. Compared with the related art, the second similarity is obtained based on the recognition of the three-dimensional face image. When the second similarity is within the interval between the lower limit value of the three-dimensional face image similarity and the upper limit value of the three-dimensional face image similarity, it is necessary to further verify the first similarity obtained based on the recognition of the two-dimensional face image. When the first similarity is greater than the first two-dimensional face image similarity threshold, the smart door lock executes unlocking. Through double verification, when the accuracy of the three-dimensional face image recognition is insufficient, the door can be unlocked by referring to the recognition result of the two-dimensional face image, which improves the adaptability of the three-dimensional face recognition to the external environment to a certain extent.

[0083] As a refinement of the embodiment of the present disclosure, after executing step 102 to identify the three-dimensional facial image and obtain the second similarity, the method can also adopt but is not limited to the following implementation methods, for example: if the second similarity is less than the lower limit value of the three-dimensional facial image similarity, unlocking is not performed; if the second similarity is greater than or equal to the upper limit value of the three-dimensional facial image similarity, unlocking is performed.

[0084] In some possible implementations of this embodiment, when it is determined that the second similarity is less than the lower limit of the similarity of the three-dimensional face image, unlocking is not performed, that is, when the second similarity is less than the lower limit of the similarity of the three-dimensional face image, it can be determined that the weight of not performing unlocking is greater than the weight of performing unlocking, and there is no need to further determine the weight relationship between performing unlocking and not performing unlocking based on the first similarity; as described above, when it is determined that the second similarity is greater than or equal to the upper limit of the similarity of the three-dimensional face image, unlocking is performed, that is, when the second similarity is greater than the upper limit of the similarity of the three-dimensional face image, it can be determined that the weight of performing unlocking is greater than the weight of not performing unlocking, and there is no need to further determine the weight relationship between performing unlocking and not performing unlocking based on the first similarity. It should be understood that this embodiment does not limit the method of weight judgment.

[0085] In some embodiments, there is a situation where finger vein recognition and the above-mentioned three-dimensional face recognition are performed in parallel. For example, after obtaining a two-dimensional face image based on a camera and recognizing the two-dimensional face image to obtain a first similarity, the method can also adopt but is not limited to responding to a recognition request for a finger vein image, recognizing the finger vein image to obtain a third similarity; if the third similarity is greater than or equal to the lower limit value of the finger vein image similarity and less than the upper limit value of the finger vein image similarity, then determine whether the first similarity is greater than the first two-dimensional face image similarity threshold; if the first similarity is greater than the first two-dimensional face image similarity threshold, then perform unlocking.

[0086] The recognition process of the finger vein recognition is similar to the recognition process of the above-mentioned three-dimensional face recognition, and the recognition processes involved in the finger vein recognition and the three-dimensional face recognition can also be applied to other biometric recognition technologies, such as: iris recognition, retina recognition, fingerprint recognition, finger vein recognition, palm vein recognition, voiceprint recognition, gait recognition, etc.

[0087] As a refinement of the finger vein recognition in the above embodiment, an exemplary description is provided herein. When a user uses finger vein recognition, a finger vein image of the user is collected based on the finger vein recognition module on the smart door lock, and then the finger vein image is compared with the finger vein image already entered in the database for similarity to obtain the third similarity, that is, the third similarity is a description of the degree of similarity between the finger vein image collected by the fingerprint recognition module and the finger vein image in the database. Furthermore, in order to realize the judgment of the degree of similarity, that is, the third similarity, a lower limit value of the finger vein image similarity, an upper limit value of the finger vein image similarity, and a first two-dimensional face image similarity threshold are set. In the finger vein image When the third similarity between the two images is in the middle range, that is, between the lower limit value of the finger vein similarity and the upper limit value of the finger vein similarity, the smart door lock cannot determine the weight relationship between executing unlocking or not executing unlocking. Therefore, the first similarity is needed to assist in determining the weight relationship between executing unlocking or not executing unlocking. That is, when the first similarity is greater than the first two-dimensional face similarity threshold, it can be determined that the weight of executing unlocking is greater than the weight of not executing unlocking, then unlocking is executed. Similar to the three-dimensional face recognition in the above embodiment, the values ​​of the lower limit value of the finger vein image similarity and the upper limit value of the finger vein image similarity can be set according to actual conditions, and this embodiment does not limit the values.

[0088] In some possible implementations of this embodiment, the second similarity obtained by the three-dimensional face recognition can also be used as a reference parameter when the finger vein recognition is used to unlock the door; conversely, the third similarity obtained by the finger vein recognition can also be used as a reference parameter when the three-dimensional face recognition is used to unlock the door. Similarly, after adding different biometric recognition technologies, more similarity values ​​will be obtained, that is, they are not limited to the first similarity, the second similarity, and the third similarity described in this embodiment. After obtaining more similarities, the combination of each similarity can provide more parameter judgments for the weight relationship judgment when a certain biometric recognition technology is used to unlock the door, and more combinations of judgment steps. Because its principle is the same as in the above embodiment, this embodiment will not be repeated for the sake of clarity and simplicity.

[0089] As a refinement of the above embodiment, after identifying the finger vein image and obtaining the third similarity, the method can also adopt but is not limited to the following implementation methods, for example: if the third similarity is less than the lower limit value of the finger vein image similarity, unlocking is not performed; if the third similarity is greater than or equal to the upper limit value of the finger vein image similarity, unlocking is performed.

[0090] When the third similarity is less than the lower limit value of the finger vein image similarity, it can be directly determined that the weight of not executing unlocking is greater than the weight of executing unlocking, and there is no need to perform weight judgment based on the first similarity, and the smart door lock can directly execute unlocking; on the contrary, when the order similarity is greater than the upper limit value of the finger vein image similarity, it can be directly determined that the weight of executing unlocking is greater than the weight of not executing unlocking, and there is no need to perform weight judgment based on the first similarity, and the smart door lock can directly not execute unlocking.

[0091] As a refinement of this embodiment, when executing step 101 to obtain a two-dimensional facial image based on a camera, the following implementation methods can be adopted but are not limited to, for example: calling a preset sensor to monitor whether the environment of a preset monitoring area has changed; if it is determined that the environment of the preset monitoring area has changed, waking up the camera; when it is determined that the camera has detected a human image, obtaining the two-dimensional facial image.

[0092] As a refinement of the above embodiment, when it is determined that the camera detects a non-human image, the camera is controlled to enter a sleep state.

[0093] The preset sensor may be an infrared pyroelectric sensor, the spatial range that can be detected by the preset sensor is a preset monitoring area, and the camera is a color camera.

[0094] As an extension of the above detailed description, this embodiment provides a scenario description. When a person walks towards the smart door lock from a distance, the preset sensor will first sense that someone is moving, and then wake up the camera. The camera will start the recording function and perform two-dimensional face recognition. It will continue to detect human figures within a certain distance range. If a human figure is detected, face recognition will be started and the two-dimensional face image will be obtained. Otherwise, it is considered to be a false awakening caused by the slightest movement. If it is a false awakening, the camera will enter sleep again. If a mask or face mask is found during the two-dimensional face detection process, the two-dimensional face detection will fail.

[0095] As a refinement of the above embodiment, before the three-dimensional face image is recognized, the following implementation method can also be used to complete the awakening of the three-dimensional face recognition, for example: determine whether the first similarity is greater than the second two-dimensional face similarity threshold; if the first similarity is greater than the second two-dimensional face similarity threshold, start the ultrasound and collect the three-dimensional face image based on the ultrasound.

[0096] The second two-dimensional face similarity threshold is a standard for determining whether to activate the ultrasonic wave. When the first similarity meets the standard, that is, the first similarity is greater than the second two-dimensional face similarity threshold, the ultrasonic wave is activated to complete the acquisition of the three-dimensional face image. In the scene, it will appear that the two-dimensional face recognition is successful. If the person continues to approach the door lock, the ultrasonic wave will be triggered, thereby activating the three-dimensional face recognition.

[0097] As an extension of the above embodiment, for users wearing masks or face shields, since they cannot use three-dimensional face recognition to unlock the door, they can only unlock the door through finger vein / fingerprint. In this case, ultrasonic wake-up is not allowed, and the three-dimensional face recognition module will not be powered on, and the overall power consumption of the door lock is optimized.

[0098] In summary, this embodiment can achieve the following effects:

[0099] 1. Based on the recognition of the three-dimensional face image, the second similarity is obtained. When the second similarity is within the interval of the lower limit value of the three-dimensional face image similarity and the upper limit value of the three-dimensional face image similarity, it is necessary to further verify the first similarity obtained based on the recognition of the two-dimensional face image. When the first similarity is greater than the first two-dimensional face image similarity threshold, the smart door lock executes unlocking. Through double verification, when the accuracy of the three-dimensional face image recognition is insufficient, the door can be unlocked by referring to the recognition result of the two-dimensional face image, which improves the adaptability of the three-dimensional face recognition to the external environment to a certain extent.

[0100] 2. For users wearing masks or face shields, since they cannot use 3D face recognition to unlock the door, they can only unlock the door through finger vein / fingerprint. In this case, ultrasonic wake-up is not allowed, and the 3D face recognition module will not be powered on, and the overall power consumption of the door lock is optimized.

[0101] Corresponding to the above-mentioned method for identifying a smart door lock, the present invention also proposes a device for identifying a smart door lock. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be repeated in the present invention.

[0102] Figure 2 A schematic diagram of the structure of another smart door lock identification device provided in an embodiment of the present disclosure, such as Figure 2 As shown, including:

[0103] A first recognition unit 21 is used to obtain a two-dimensional face image based on a camera, and recognize the two-dimensional face image to obtain a first similarity;

[0104] A second recognition unit 22, configured to recognize the three-dimensional face image in response to a recognition request of the three-dimensional face image, and obtain a second similarity;

[0105] A first judging unit 23, configured to judge whether the first similarity is greater than a first two-dimensional face image similarity threshold when the second similarity is greater than or equal to a three-dimensional face image similarity lower limit and less than a three-dimensional face image similarity upper limit;

[0106] The first execution unit 24 executes unlocking when the first similarity is greater than the first two-dimensional face image similarity threshold.

[0107] The present invention discloses a device for identifying a smart door lock, and its main technical scheme includes: obtaining a two-dimensional face image based on a camera, and identifying the two-dimensional face image to obtain a first similarity; in response to a request for identifying a three-dimensional face image, identifying the three-dimensional face image to obtain a second similarity; if the second similarity is greater than or equal to a lower limit value of the three-dimensional face image similarity and less than an upper limit value of the three-dimensional face image similarity, determining whether the first similarity is greater than a first two-dimensional face image similarity threshold; if the first similarity is greater than the first two-dimensional face image similarity threshold, unlocking is performed. Compared with the related art, the second similarity is obtained based on the recognition of the three-dimensional face image. When the second similarity is within the interval between the lower limit value of the three-dimensional face image similarity and the upper limit value of the three-dimensional face image similarity, it is necessary to further verify the first similarity obtained based on the recognition of the two-dimensional face image. When the first similarity is greater than the first two-dimensional face image similarity threshold, the smart door lock executes unlocking. Through double verification, when the accuracy of the three-dimensional face image recognition is insufficient, the door can be unlocked by referring to the recognition result of the two-dimensional face image, which improves the adaptability of the three-dimensional face recognition to the external environment to a certain extent.

[0108] Figure 3 A schematic diagram of the structure of another device for identifying a smart door lock provided in an embodiment of the present disclosure. Further, in a possible implementation of the present embodiment, as Figure 3 As shown, the first execution unit 24 is also used for:

[0109] When the second similarity is less than the lower limit of the three-dimensional face image similarity, unlocking is not performed;

[0110] When the second similarity is greater than or equal to the upper limit of the similarity of the three-dimensional face image, unlocking is performed.

[0111] Optionally, the device further comprises:

[0112] A third recognition unit 25 is used to recognize the finger vein image in response to the recognition request of the finger vein image to obtain a third similarity;

[0113] A second judgment unit 26, configured to judge whether the first similarity is greater than a first two-dimensional face image similarity threshold when the third similarity is greater than or equal to a finger vein image similarity lower limit and less than a finger vein image similarity upper limit;

[0114] The second execution unit 27 is configured to execute unlocking when the first similarity is greater than the first two-dimensional face image similarity threshold.

[0115] Optionally, the second execution unit 27 is further configured to:

[0116] When the third similarity is less than the finger vein image similarity lower limit, unlocking is not performed;

[0117] When the third similarity is greater than or equal to the finger vein image similarity upper limit value, unlocking is performed.

[0118] Optionally, the first identification unit 21 includes:

[0119] The calling module 211 is used to call the preset sensor to monitor whether the environment of the preset monitoring area changes;

[0120] A wake-up module 212 is used to wake up the camera when it is determined that the environment of the preset monitoring area has changed;

[0121] The acquisition module 213 is used to acquire the two-dimensional human face image when it is determined that the camera detects a human image.

[0122] Optionally, the device further comprises:

[0123] The control unit 28 is used to control the camera to enter a dormant state when it is determined that the camera detects a non-human image.

[0124] Optionally, the device further comprises:

[0125] A third judging unit 29, configured to judge whether the first similarity is greater than a second two-dimensional face similarity threshold;

[0126] The second identification unit 22 is further used for:

[0127] When the first similarity is greater than the second two-dimensional face similarity threshold, ultrasound is started, and the three-dimensional face image is collected based on the ultrasound.

[0128] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and the principle is the same, which is not limited in this embodiment.

[0129] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0130] Figure 4A schematic block diagram of an example electronic device 300 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0131] like Figure 4 As shown, the device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 302 or a computer program loaded from a storage unit 308 to a RAM (Random Access Memory) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0132] A number of components in the device 300 are connected to the I / O interface 305, including: an input unit 303, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0133] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the method for identifying a smart door lock. For example, in some embodiments, the method for identifying a smart door lock may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to execute the aforementioned method of identifying the smart door lock in any other appropriate manner (eg, by means of firmware).

[0134] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a dedicated or general-purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0135] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0136] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0137] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0138] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0139] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0140] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0141] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0142] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for identifying a smart door lock, characterized in that: include: Acquire a two-dimensional face image based on a camera, and recognize the two-dimensional face image to obtain a first similarity; In response to a recognition request for a three-dimensional face image, determining whether the first similarity is greater than a second two-dimensional face similarity threshold; if the first similarity is greater than the second two-dimensional face similarity threshold, starting ultrasound, collecting the three-dimensional face image based on the ultrasound, recognizing the three-dimensional face image, and obtaining a second similarity; If the second similarity is greater than or equal to a lower limit of the three-dimensional face image similarity and less than an upper limit of the three-dimensional face image similarity, determining whether the first similarity is greater than a first two-dimensional face image similarity threshold; If the first similarity is greater than the first two-dimensional face image similarity threshold, unlocking is performed.

2. The method according to claim 1, characterized in that After the three-dimensional face image is recognized and the second similarity is obtained, the method further includes: If the second similarity is less than the lower limit of the three-dimensional face image similarity, unlocking is not performed; If the second similarity is greater than or equal to the upper limit of the similarity of the three-dimensional face image, unlocking is performed.

3. The method according to claim 1, characterized in that The method of acquiring a two-dimensional face image based on a camera includes: Call the preset sensor to monitor whether the environment of the preset monitoring area has changed; If it is determined that the environment of the preset monitoring area has changed, waking up the camera; When it is determined that the camera detects a human-shaped image, the two-dimensional human face image is acquired.

4. The method according to claim 3, characterized in that: After waking up the camera, the method further includes: When it is determined that the camera detects a non-human image, the camera is controlled to enter a dormant state.

5. A device for identifying a smart door lock, characterized in that: include: A first recognition unit, configured to obtain a two-dimensional face image based on a camera, and recognize the two-dimensional face image to obtain a first similarity; a second recognition unit, configured to, in response to a recognition request for a three-dimensional face image, determine whether the first similarity is greater than a second two-dimensional face similarity threshold; If the first similarity is greater than the second two-dimensional face similarity threshold, start the ultrasonic wave, collect the three-dimensional face image based on the ultrasonic wave, recognize the three-dimensional face image, and obtain the second similarity; A first judging unit, configured to judge whether the first similarity is greater than a first two-dimensional face image similarity threshold when the second similarity is greater than or equal to a three-dimensional face image similarity lower limit and less than a three-dimensional face image similarity upper limit; The first execution unit executes unlocking when the first similarity is greater than the first two-dimensional face image similarity threshold.

6. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-4.

8. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 4.

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