Gesture awakening method and device and storage medium

Abstract

The invention relates to the technical field of image processing, in particular to a gesture awakening method and device and a storage medium. Comprising the following steps: acquiring a gesture category, depth information and at least one hand key point corresponding to a gesture image; when the gesture category is a wake-up gesture, determining a depth difference of a target area in the gesture image according to the depth information; the target area comprises an area within a first preset distance by taking a hand in the gesture image as a center; when the depth difference is not zero, determining the relative depth of each hand key point based on the at least one hand key point and the depth information; and when the relative depth of each hand key point is greater than a depth threshold value, awakening the screen of the electronic equipment. The embodiment of the invention is used for solving the problem of false wake-up in gesture wake-up.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a gesture wake-up method, device and storage medium. Background Art

[0002] Gesture wake-up refers to waking up a device or system by recognizing specific gestures or actions, so that it can resume normal operation from sleep or standby mode. Gesture wake-up is usually used in smart devices or virtual reality devices to provide users with a more convenient way of interaction.

[0003] At present, the gesture wake-up method of smart devices usually uses a training data set to train a deep neural network model, and then uses the trained deep neural network model to recognize the wake-up gesture on the collected gesture image to obtain the recognition result, and then determines whether the device needs to be woken up based on the recognition result. However, due to the uncertainty of user actions, actions similar to the wake-up gesture may also cause the device to be woken up by mistake, resulting in a poor user experience. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a gesture wake-up method, device and storage medium, which can improve the accuracy of gesture wake-up.

[0005] In a first aspect, the present application provides a gesture wake-up method, which is applied to an electronic device, including: obtaining a gesture category, depth information, and at least one hand key point corresponding to a gesture image; when the gesture category is a wake-up gesture, determining the depth difference of a target area in the gesture image based on the depth information; the target area includes an area within a first preset distance centered on the hand in the gesture image; when the depth difference is not zero, determining the relative depth of each hand key point based on at least one hand key point and the depth information; when the relative depth of each hand key point is greater than a depth threshold, waking up the screen of the electronic device.

[0006] In some embodiments, determining the depth difference of the target area in the gesture image according to the depth information includes: determining maximum depth information and minimum depth information in the target area; and determining the difference between the maximum depth information and the minimum depth information as the depth difference of the target area.

[0007] In some embodiments, based on at least one hand key point and depth information, the relative depth of each hand key point is determined, including: performing processing operations on at least one hand key point and depth information to obtain the relative depth of each hand key point; the processing operations include: determining the difference between the first depth information and each depth information in the first area; determining the maximum difference as the relative depth of the first key point; the first depth information is the depth information of the first key point; the first key point is any hand key point among the at least one hand key point; the first area includes an area within a second preset distance centered on the first key point.

[0008] In some embodiments, after acquiring the gesture category, depth information, and at least one hand key point corresponding to the gesture image, the method also includes: when the gesture category, depth information, and at least one hand key point meet at least one of the following preset conditions, not responding to the user gesture corresponding to the gesture image; wherein the preset conditions include: the gesture category is not a wake-up gesture; the depth difference is zero; the relative depth of any hand key point is less than or equal to the depth threshold.

[0009] In some embodiments, obtaining a gesture category, depth information, and at least one hand key point corresponding to a gesture image includes: collecting a gesture image; identifying a gesture category and at least one hand key point corresponding to the gesture image; and extracting depth information of the gesture image.

[0010] In some embodiments, identifying a gesture category and at least one hand key point corresponding to a gesture image includes: using a gesture recognition model to identify the gesture category corresponding to the gesture image; the gesture recognition model is pre-trained based on historical gesture images and gesture categories corresponding to the historical gesture images; using a key point recognition model to identify at least one hand key point corresponding to the gesture image; the key point recognition model is pre-trained based on historical gesture images and hand key points corresponding to the historical gesture images.

[0011] In the second aspect, the present application provides a gesture wake-up device, which is applied to an electronic device, including: an acquisition module, used to obtain a gesture category, depth information, and at least one hand key point corresponding to a gesture image; a processing module, used to determine the depth difference of a target area in the gesture image according to the depth information when the gesture category is a wake-up gesture; the target area includes an area within a first preset distance centered on the hand in the gesture image; the processing module is also used to determine the relative depth of each hand key point based on at least one hand key point and the depth information when the depth difference is not zero; a wake-up module, used to wake up the screen of the electronic device when the relative depth of each hand key point is greater than a depth threshold.

[0012] In some embodiments, the processing module is specifically used to: determine maximum depth information and minimum depth information in the target area; and determine the difference between the maximum depth information and the minimum depth information as the depth difference of the target area.

[0013] In some embodiments, the processing module is specifically used to: perform processing operations on at least one hand key point and depth information to obtain the relative depth of each hand key point; the processing operations include: determining the difference between the first depth information and each depth information in the first area; determining the maximum difference as the relative depth of the first key point; the first depth information is the depth information of the first key point; the first key point is any hand key point among the at least one hand key point; the first area includes an area within a second preset distance centered on the first key point.

[0014] In some embodiments, the processing module is also used to: after acquiring the gesture category, depth information, and at least one hand key point corresponding to the gesture image, not respond to the user gesture corresponding to the gesture image when the gesture category, depth information, and at least one hand key point meet at least one of the following preset conditions; wherein the preset conditions include: the gesture category is not a wake-up gesture; the depth difference is zero; the relative depth of any hand key point is less than or equal to the depth threshold.

[0015] In some embodiments, the acquisition module is specifically used to: collect gesture images; identify the gesture category and at least one hand key point corresponding to the gesture image; and extract depth information of the gesture image.

[0016] In some embodiments, the acquisition module is specifically used to: use a gesture recognition model to identify the gesture category corresponding to the gesture image; the gesture recognition model is pre-trained based on historical gesture images and the gesture categories corresponding to the historical gesture images; use a key point recognition model to identify at least one hand key point corresponding to the gesture image; the key point recognition model is pre-trained based on historical gesture images and the hand key points corresponding to the historical gesture images.

[0017] In a third aspect, the present application provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the gesture wake-up method of the first aspect is implemented.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium, including: a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the gesture wake-up method of the first aspect is implemented.

[0019] In a fifth aspect, the present application provides a computer program product, comprising: when the computer program product is run on a computer, the computer implements the gesture wake-up method as in the first aspect.

[0020] The technical solution provided by the present application has the following advantages compared with the prior art: first, the gesture category, depth information, and at least one hand key point corresponding to the gesture image are obtained, and when the gesture category is a wake-up gesture, the depth difference of the target area in the gesture image is determined according to the depth information. Afterwards, when the depth difference is not zero, the relative depth of each hand key point is determined based on at least one hand key point and the depth information. Finally, when the relative depth of each hand key point is greater than the depth threshold, the screen of the electronic device is woken up. In this way, first, when the gesture category is identified as a wake-up gesture, the screen of the electronic device is not directly woken up, but whether there is a depth difference in the hand area is determined by the depth information in the gesture image, and the screen of the electronic device is woken up only when the relative depths of the hand key points are greater than the depth threshold. In general, the relative depth of the hand key points of the wake-up gesture is large, and the relative depth of the hand key points of the non-wake-up gesture is small, so based on this, the screen of the electronic device can be accurately woken up, reducing the probability of the electronic device being woken up by mistake. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0023] Figure 1 One of the flowcharts of the gesture wake-up method provided in the embodiment of the present application;

[0024] Figure 2 The second flowchart of the gesture wake-up method provided in the embodiment of the present application;

[0025] Figure 3 The third flowchart of the gesture wake-up method provided in the embodiment of the present application;

[0026] Figure 4 A schematic diagram of key points of a hand provided in an embodiment of the present application;

[0027] Figure 5 The fourth flowchart of the gesture wake-up method provided in the embodiment of the present application;

[0028] Figure 6 One of the schematic diagrams of a gesture image is provided for an embodiment of the present application;

[0029] Figure 7 A second schematic diagram of a gesture image is provided for an embodiment of the present application;

[0030] Figure 8 The fifth flowchart of the gesture wake-up method provided in the embodiment of the present application;

[0031] Fig. 9 A schematic diagram of the structure of a gesture awakening device provided in an embodiment of the present application;

[0032] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to more clearly understand the above-mentioned purposes, features and advantages of the present application, the scheme of the present application will be further described below. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0034] In the following description, many specific details are set forth to facilitate a full understanding of the present application, but the present application may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only part of the embodiments of the present application, rather than all of the embodiments.

[0035] At present, the gesture wake-up method of smart devices usually uses a training data set to train a deep neural network model, and then uses the trained deep neural network model to recognize the wake-up gesture on the collected gesture image to obtain the recognition result, and then determines whether the device needs to be woken up based on the recognition result. However, due to the uncertainty of user actions, actions similar to the wake-up gesture may also cause the device to be woken up by mistake, resulting in a poor user experience.

[0036] The embodiment of the present application provides a gesture wake-up method, which can obtain the gesture category, depth information, and at least one hand key point corresponding to the gesture image, and when the gesture category is a wake-up gesture, determine the depth difference of the target area in the gesture image according to the depth information. Afterwards, when the depth difference is not zero, the relative depth of each hand key point is determined based on at least one hand key point and the depth information. Finally, when the relative depth of each hand key point is greater than the depth threshold, the screen of the electronic device is woken up. This avoids the electronic device from being woken up by mistake and improves the user experience.

[0037] The gesture wake-up method provided in the embodiment of the present application can be implemented by a gesture wake-up device, and the gesture wake-up device provided in the embodiment of the present application can be hardware or software. When the gesture wake-up device is hardware, it can be various electronic devices with a gesture wake-up function, including but not limited to vehicle-mounted equipment, smart vehicles, mobile phones, computers, smart TVs, wearable devices, etc. When the gesture wake-up device is software, it can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules, or as a single software or software module, which is not specifically limited here.

[0038] Figure 1 A flowchart of a gesture wake-up method provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the gesture wake-up method may include the following steps.

[0039] S11. Obtain a gesture category, depth information, and at least one hand key point corresponding to the gesture image.

[0040] In some embodiments, Figure 2 As shown, the method of obtaining the gesture category, depth information, and at least one hand key point corresponding to the gesture image may include the following steps:

[0041] S111. Collect gesture images.

[0042] In some embodiments, the gesture image may be acquired by using an image acquisition device that can acquire depth information, such as a stereo camera, a depth camera, and the like.

[0043] S112: Identify a gesture category and at least one hand key point corresponding to the gesture image.

[0044] In some embodiments, Figure 3 As shown, the method of identifying the gesture category and at least one hand key point corresponding to the gesture image may include the following steps:

[0045] S1121. Use a gesture recognition model to identify a gesture category corresponding to the gesture image.

[0046] The gesture recognition model is pre-trained based on historical gesture images and gesture categories corresponding to the historical gesture images. The historical gesture images are gesture images collected before the gesture images are collected.

[0047] Specifically, a method of using the gesture recognition model to recognize the gesture category corresponding to the gesture image may be to input the gesture image into the gesture recognition model to obtain the gesture category corresponding to the gesture image.

[0048] S1122: Use a key point recognition model to recognize at least one hand key point corresponding to the gesture image.

[0049] The key point recognition model is pre-trained based on the historical gesture images and the hand key points corresponding to the historical gesture images. The hand key points at least include the key points of the outermost circle of the hand. For example, Figure 4 A schematic diagram of a hand key point provided in an embodiment of the present application, such as Figure 4 As shown, the hand key points include 13 key points such as fingertips and wrists. Of course, the number of hand key points is not limited in this application. In actual applications, relevant personnel can set specific values ​​of hand key points according to actual conditions. For example, if you want to make gesture wake-up more accurate and lower the false wake-up rate, you can set more hand key points; if you want to achieve a faster gesture wake-up effect, you can set fewer hand key points.

[0050] Specifically, a method of using a key point recognition model to recognize at least one hand key point corresponding to a gesture image may be to input the gesture image into the key point recognition model to obtain at least one hand key point corresponding to the gesture image.

[0051] In some embodiments, the method of obtaining at least one hand key point may also be to use a key point extraction algorithm to extract the hand key points in the gesture image. For example, the key point extraction algorithm may be a YOLO (You Only Look Once) algorithm.

[0052] S113: Extracting depth information of the gesture image.

[0053] In some embodiments, the depth information of the gesture image may be extracted by using a depth information extraction model, wherein the depth information extraction model is pre-trained based on historical gesture images and depth information corresponding to the historical gesture images.

[0054] In some embodiments, the depth information of the gesture image may be extracted by using a depth information extraction algorithm, for example, a stereo vision method, a time-of-flight method, a structured light method, etc.

[0055] In some embodiments, the depth information of the gesture image may be extracted by directly acquiring the depth information of the gesture image from an image acquisition device that acquires the gesture image.

[0056] S12: When the gesture category is a wake-up gesture, determine a depth difference of a target area in the gesture image according to the depth information.

[0057] The target area includes an area within a first preset distance centered on the hand in the gesture image. The first preset distance is preset, for example, a default value, or a value set by relevant personnel according to actual conditions.

[0058] In some embodiments, the wake-up gesture refers to a gesture of extending a palm with the palm facing the screen.

[0059] In some embodiments, Figure 5 As shown, the method of determining the depth difference of the target area in the gesture image according to the depth information may include the following steps:

[0060] S121 : Determine maximum depth information and minimum depth information in the target area.

[0061] Specifically, the depth information refers to the distance between each point in the gesture image and the camera, that is, the depth information of the gesture image describes the position of the object in the gesture image in the three-dimensional space. In this way, the maximum depth information and the minimum depth information in the target area are determined, that is, the depth information of the point with the largest distance from the camera and the depth information of the point with the smallest distance from the camera are determined.

[0062] S122: Determine the difference between the maximum depth information and the minimum depth information as the depth difference of the target area.

[0063] In this way, when the depth difference is zero, it is determined that the user's hand is completely against a body part or other object, and at this time it is determined that the user does not want to perform the wake-up gesture.

[0064] For example, Figure 6 A schematic diagram of a gesture image provided in an embodiment of the present application, such as Figure 6 As shown, the user's hand is completely pressed against other objects, and the depth difference of the target area is zero at this time.

[0065] When the depth difference is not zero, it includes that the user's hand is not completely against the body part or other objects, for example, the user puts his hand on the door handle and touches the face or head. It also includes that the user's hand is in the air. In this case, it is determined that the user may perform a wake-up gesture.

[0066] Figure 7 A schematic diagram of another gesture image provided in an embodiment of the present application, such as Figure 7 As shown, if the user's two fingers are marking other objects, the depth information of the blank points next to the other fingers must be greater than the depth information of the points at the hand and other objects. At this time, the depth difference of the target area is not zero.

[0067] S13. When the depth difference is not zero, determine the relative depth of each hand key point based on at least one hand key point and the depth information.

[0068] In some embodiments, based on at least one hand key point and depth information, a method for determining the relative depth of each hand key point may be: performing processing operations on at least one hand key point and depth information to obtain the relative depth of each hand key point.

[0069] The processing operation includes: first, determining the difference between the first depth information and each depth information in the first area, and then determining the maximum difference as the relative depth of the first key point. The first depth information is the depth information of the first key point; the first key point is any hand key point of at least one hand key point; the first area includes an area within a second preset distance centered on the first key point. The second preset distance is preset, for example, a default value, or a value set by a relevant person according to actual conditions.

[0070] S14. When the relative depth of each hand key point is greater than the depth threshold, wake up the screen of the electronic device.

[0071] The depth threshold is preset, for example, a default value, or a value set by relevant personnel according to actual conditions. For another example, the depth threshold is 5 cm.

[0072] In the above scheme, the gesture category, depth information, and at least one hand key point corresponding to the gesture image are obtained, and when the gesture category is a wake-up gesture, the depth difference of the target area in the gesture image is determined according to the depth information. Afterwards, when the depth difference is not zero, the relative depth of each hand key point is determined based on at least one hand key point and the depth information. Finally, when the relative depth of each hand key point is greater than the depth threshold, the screen of the electronic device is awakened. In this way, first, when the gesture category is identified as a wake-up gesture, the screen of the electronic device is not directly awakened, but whether there is a depth difference in the hand area is determined by the depth information in the gesture image. When there is no depth difference in the hand area, it is determined that the user's hand is completely attached to the body part or other objects. At this time, it is determined that the user does not want to perform the wake-up gesture, which avoids the electronic device from being woken up by mistake and improves the user experience. Afterwards, when there is a depth difference in the hand area, it is further determined whether the relative depth of the hand key point is greater than the depth threshold, and when the relative depth of any hand key point is less than or equal to the depth threshold, it is determined that there are other objects near the user's hand, then the user may want to operate other objects, not to wake up the electronic device, further avoiding the electronic device from being woken up by mistake and improving the user experience. Finally, when the relative depths of the key points of the hand are greater than the depth threshold, the screen of the electronic device is awakened, thereby reducing the probability of the electronic device being woken up by mistake, indirectly increasing the life of the electronic device and protecting the rights and interests of users.

[0073] In some embodiments, Figure 8As shown, after obtaining the gesture category, depth information, and at least one hand key point corresponding to the gesture image, the method further includes:

[0074] S15: When the gesture category, the depth information, and at least one hand key point satisfy at least one of the following preset conditions, do not respond to the user gesture corresponding to the gesture image.

[0075] Among them, the preset conditions include: the gesture category is not a wake-up gesture; the depth difference is zero; the relative depth of any hand key point is less than or equal to the depth threshold.

[0076] In the above scheme, when the gesture category is not a wake-up gesture, or the depth difference is zero, or the relative depth of any hand key point is less than or equal to the depth threshold, the user gesture corresponding to the gesture image is not responded. In this way, when the gesture category is identified as a wake-up gesture, the screen of the electronic device is not directly woken up, but the depth information in the gesture image is used to determine whether there is a depth difference in the hand area. When there is no depth difference in the hand area, it is determined that the user's hand is completely against the body part or other objects. At this time, it is determined that the user does not want to perform the wake-up gesture, which avoids the electronic device from being woken up by mistake and improves the user experience. Afterwards, when there is a depth difference in the hand area, it is further determined whether the relative depth of the hand key point is greater than the depth threshold, and when the relative depth of any hand key point is less than or equal to the depth threshold, it is determined that there are other objects near the user's hand, then the user may want to operate other objects, not to wake up the electronic device, which further avoids the electronic device from being woken up by mistake and improves the user experience.

[0077] The embodiment of the present application can divide the functional modules of the gesture wake-up device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0078] like Fig. 9 , which is a schematic diagram of the structure of a gesture awakening device 200 provided in an embodiment of the present application. The gesture awakening device 200 is applied to an electronic device and includes an acquisition module 201, a processing module 202, and a awakening module 203.

[0079] The acquisition module 201 is used to obtain the gesture category, depth information, and at least one hand key point corresponding to the gesture image; the processing module 202 is used to determine the depth difference of the target area in the gesture image according to the depth information when the gesture category is a wake-up gesture; the target area includes an area within a first preset distance centered on the hand in the gesture image; the processing module 202 is also used to determine the relative depth of each hand key point based on at least one hand key point and the depth information when the depth difference is not zero; the wake-up module 203 is used to wake up the screen of the electronic device when the relative depth of each hand key point is greater than the depth threshold.

[0080] In some embodiments, the processing module 202 is specifically used to: determine maximum depth information and minimum depth information in the target area; and determine the difference between the maximum depth information and the minimum depth information as the depth difference of the target area.

[0081] In some embodiments, the processing module 202 is specifically used to: perform processing operations on at least one hand key point and depth information to obtain the relative depth of each hand key point; the processing operations include: determining the difference between the first depth information and each depth information in the first area; determining the maximum difference as the relative depth of the first key point; the first depth information is the depth information of the first key point; the first key point is any hand key point among the at least one hand key point; the first area includes an area within a second preset distance centered on the first key point.

[0082] In some embodiments, the processing module 202 is also used to: after obtaining the gesture category, depth information, and at least one hand key point corresponding to the gesture image, not respond to the user gesture corresponding to the gesture image when the gesture category, depth information, and at least one hand key point meet at least one of the following preset conditions; wherein the preset conditions include: the gesture category is not a wake-up gesture; the depth difference is zero; the relative depth of any hand key point is less than or equal to the depth threshold.

[0083] In some embodiments, the acquisition module 201 is specifically used to: collect a gesture image; identify a gesture category and at least one hand key point corresponding to the gesture image; and extract depth information of the gesture image.

[0084] In some embodiments, the acquisition module 201 is specifically used to: use a gesture recognition model to identify the gesture category corresponding to the gesture image; the gesture recognition model is pre-trained based on historical gesture images and the gesture categories corresponding to the historical gesture images; use a key point recognition model to identify at least one hand key point corresponding to the gesture image; the key point recognition model is pre-trained based on historical gesture images and the hand key points corresponding to the historical gesture images.

[0085] The gesture awakening device provided in this embodiment can execute the gesture awakening method provided in the above method embodiment. Its implementation principle and technical effect are similar to those of the above method and will not be repeated here.

[0086] Fig.10 An electronic device provided in an embodiment of the present application may include a processor 302, and the processor 302 is used to execute application code to implement the gesture wake-up method in the present application.

[0087] The processor 302 may be a central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the present application.

[0088] like Fig.10 As shown, the electronic device may further include a memory 303. The memory 303 is used to store application program codes for executing the solution of the present application, and the execution is controlled by the processor 302.

[0089] The memory 303 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 303 may exist independently and be connected to the processor 302 via the bus 304. The memory 303 may also be integrated with the processor 302.

[0090] like Fig.10 As shown, the electronic device may further include a communication interface 301, wherein the communication interface 301, the processor 302, and the memory 303 may be coupled to each other, for example, via a bus 304. The communication interface 301 is used to exchange information with other devices, for example, to support information exchange between the electronic device and other devices.

[0091] It should be pointed out that Fig.10 The device structure shown in the figure does not constitute a limitation on the electronic device, except Fig.10 In addition to the components shown, the electronic device may include more or fewer components than shown, or combine certain components, or arrange the components differently. The electronic device provided in this embodiment can execute the gesture wake-up method provided in the above method embodiment, and its implementation principle and technical effect are similar to the above method, which will not be repeated here.

[0092] An embodiment of the present application provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the various processes of the gesture wake-up method in the above method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0093] The computer readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0094] An embodiment of the present application provides a computer program product, which stores a computer program. When the computer program is executed by a processor, the various processes of the gesture wake-up method in the above method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0095] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media that include computer-usable program code.

[0096] In the present application, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0097] In this application, memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0098] In this application, computer-readable media includes permanent and non-permanent, removable and non-removable storage media. Storage media can be implemented by any method or technology to store information, and the information can be computer-readable instructions, data structures, modules of programs or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. According to the definition in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data and carrier waves.

[0099] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0100] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A gesture wake-up method, applied to an electronic device, characterized in that: include: Obtaining a gesture category, depth information, and at least one hand key point corresponding to the gesture image; When the gesture category is a wake-up gesture, determining a depth difference of a target area in the gesture image according to the depth information; the target area includes an area within a first preset distance centered on the hand in the gesture image; When the depth difference is not zero, determining a relative depth of each hand key point based on the at least one hand key point and the depth information; When the relative depth of each of the hand key points is greater than a depth threshold, the screen of the electronic device is woken up.

2. The gesture wake-up method according to claim 1, characterized in that: The determining the depth difference of the target area in the gesture image according to the depth information includes: Determine maximum depth information and minimum depth information in the target area; A difference between the maximum depth information and the minimum depth information is determined as a depth difference of the target area.

3. The gesture wake-up method according to claim 1, characterized in that: The determining the relative depth of each hand key point based on the at least one hand key point and the depth information includes: Performing processing operations on the at least one hand key point and the depth information to obtain a relative depth of each hand key point; The processing operation includes: determining the difference between the first depth information and each depth information in the first area; determining the maximum difference as the relative depth of the first key point; the first depth information is the depth information of the first key point; the first key point is any hand key point among the at least one hand key point; the first area includes an area within a second preset distance centered on the first key point.

4. The gesture wake-up method according to claim 1, characterized in that: After obtaining the gesture category, depth information, and at least one hand key point corresponding to the gesture image, the method further includes: When the gesture category, the depth information, and at least one hand key point meet at least one of the following preset conditions, do not respond to the user gesture corresponding to the gesture image; Among them, the preset conditions include: the gesture category is not a wake-up gesture; the depth difference is zero; the relative depth of any hand key point is less than or equal to a depth threshold.

5. The gesture wake-up method according to claim 1, characterized in that: The step of obtaining a gesture category, depth information, and at least one hand key point corresponding to the gesture image includes: Collecting gesture images; Identify a gesture category and at least one hand key point corresponding to the gesture image; Depth information of the gesture image is extracted.

6. The gesture wake-up method according to claim 5, characterized in that: The identifying the gesture category and at least one hand key point corresponding to the gesture image includes: Using a gesture recognition model to identify the gesture category corresponding to the gesture image; the gesture recognition model is pre-trained based on historical gesture images and gesture categories corresponding to the historical gesture images; A key point recognition model is used to recognize at least one hand key point corresponding to the gesture image; the key point recognition model is pre-trained based on historical gesture images and the hand key points corresponding to the historical gesture images.

7. A gesture awakening device, applied to an electronic device, characterized in that: include: An acquisition module, used to acquire a gesture category, depth information, and at least one hand key point corresponding to the gesture image; a processing module, configured to determine, when the gesture category is a wake-up gesture, a depth difference of a target area in the gesture image according to the depth information; the target area includes an area within a first preset distance centered on the hand in the gesture image; The processing module is further configured to determine the relative depth of each hand key point based on the at least one hand key point and the depth information when the depth difference is not zero; The wake-up module is used to wake up the screen of the electronic device when the relative depth of each of the hand key points is greater than a depth threshold.

8. The gesture awakening device according to claim 7, characterized in that: The processing module is specifically used for: Determine maximum depth information and minimum depth information in the target area; A difference between the maximum depth information and the minimum depth information is determined as a depth difference of the target area.

9. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the gesture wake-up method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: include: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the gesture wake-up method according to any one of claims 1 to 6 is implemented.

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