Method, apparatus, device, readable medium and program product for sitting posture detection

Abstract

The invention discloses a sitting posture detection method, device and equipment, a computer readable medium and a program product, and belongs to the technical field of computers. The sitting posture detection method comprises the following steps: acquiring a standard face line of a target user; in response to a face image of a target user detected in the target picture, performing face information extraction on the face image to obtain face information; according to the standard face line and the face information, determining sitting posture information of the target user; and generating target prompt information according to the sitting posture information and sending the target prompt information to the target user equipment. According to the invention, through analyzing the face disappearance condition, the missing report condition is reduced, the accuracy of the algorithm is improved, a correct sitting posture alarm can be given, and the accuracy of sitting posture detection is improved.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a method, apparatus, device, computer-readable medium, and program product for sitting posture detection. Background Art

[0002] In today's society, people are increasingly aware of the importance of good health, especially for growing children and hardworking young people. Whether at work or in school, it's crucial to develop good sitting habits. Good sitting habits can reduce myopia in children, relieve spinal pressure, and avoid back pain, cervical fatigue, and other issues caused by poor posture, ultimately promoting better health.

[0003] The existing technology mainly adopts the following methods:

[0004] 1. Using the human body key point detection method, the sitting posture is determined by determining the position of key points. This technology requires programming complex logical relationships based on the relative positions of key points. The specific implementation process is complex, and the logical rules are easily restricted by the scene.

[0005] 2. Using the deep learning model method, the judgment of sitting posture is realized by training the deep learning model. It is necessary to collect a large amount of sitting posture data to train the model, which increases the cost.

[0006] 3. Using face detection, patent CN113486789A issues a posture abnormality alert when the detected face area exceeds the specified range, but fails to provide a correct posture determination when the face disappears. Patent CN113313917B requires consideration of the face's spatial position and angle when registering a standard sitting posture, which can easily lead to registration failure. Patent CN113313917B also addresses false positives when there is no target by determining whether there is a face in the current image, which can easily lead to missed detections of faces due to non-standard sitting postures.

[0007] It can be seen that there is an urgent need to develop a new sitting posture detection method to solve the current defects and shortcomings. Summary of the Invention

[0008] The content of this disclosure is used to briefly introduce concepts that will be described in detail in the detailed description section below. The content of this disclosure is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0009] Some embodiments of the present disclosure provide a method, apparatus, device, computer-readable medium, and program product for sitting posture detection to at least partially solve the technical problems mentioned in the above background technology section.

[0010] In a first aspect, some embodiments of the present disclosure provide a method for sitting posture detection, the method comprising: obtaining a standard facial line of a target user; in response to detecting a facial image of the target user in a target screen, extracting facial information from the facial image to obtain facial information; determining the sitting posture information of the target user based on the standard facial line and the facial information; generating target prompt information based on the sitting posture information and sending the target prompt information to the target user device.

[0011] In a second aspect, some embodiments of the present disclosure provide a device for sitting posture detection, the device comprising: an acquisition unit, configured to acquire the standard facial line of a target user; an extraction unit, configured to extract facial information from the facial image in response to detecting a facial image of the target user in a target screen, to obtain facial information; a determination unit, configured to determine the sitting posture information of the target user based on the standard facial line and the facial information; a generation unit, configured to generate target prompt information based on the sitting posture information and send the target prompt information to the target user device.

[0012] In a third aspect, an embodiment of the present application provides an electronic device comprising: one or more processors; a storage device for storing one or more programs; and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any implementation manner in the first aspect.

[0014] In a fifth aspect, some embodiments of the present disclosure provide a computer program product, including a computer program, which implements the method described in any implementation manner in the first aspect when executed by a processor.

[0015] One of the above-mentioned embodiments of the present disclosure has the following beneficial effects: by using the user to draw a line to determine the standard sitting posture, an accurate standard sitting posture can be quickly obtained, thereby improving the accuracy of determining the standard sitting posture. Two situations where there is no face in the picture are analyzed: the disappearance of the face due to a non-standard sitting posture and the target being out of the frame. An abnormal sitting posture alarm is triggered when the face disappears due to a non-standard sitting posture, while no abnormal sitting posture alarm is triggered when the target is out of the frame. By analyzing the disappearance of the face, missed reports are reduced, the accuracy of the algorithm is improved, and a correct sitting posture alarm can be triggered, thereby improving the accuracy of sitting posture detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0017] Figure 1 is a flow chart of some embodiments of a method for sitting posture detection according to the present disclosure;

[0018] Figure 2 is a flowchart of a sitting posture detection method according to some embodiments of the present disclosure

[0019] Figure 3 is a schematic structural diagram of some embodiments of the device for sitting posture detection according to the present disclosure;

[0020] Figure 4 It is a structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0021] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0022] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other.

[0023] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0024] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0025] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0026] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0027] refer to Figure 1 , shows a process 100 of some embodiments of the method for sitting posture detection according to the present disclosure. The method for sitting posture detection includes the following steps:

[0028] Step 101: Obtain the standard facial line of the target user.

[0029] In some embodiments, an executing entity (eg, an electronic device) of the method for sitting posture detection may obtain a standard facial line of the target user.

[0030] Here, the target user generally refers to a user for whom sitting posture detection is required. The standard face line generally refers to a line used to identify the position of the user's face in a standard sitting posture.

[0031] As an example, the standard face line may be the position line of the chin of the user's face in a standard sitting posture. As another example, the standard face line may also be the contour line of the user's face in a standard sitting posture.

[0032] It should be noted that the electronic device described above can be either hardware or software. When the electronic device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the electronic device is embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, or as a single software or software module. No specific limitations are given here.

[0033] In some optional implementations of some embodiments, the standard face line may be obtained in the following manner:

[0034] In response to detecting the face image of the target user in the target picture, obtaining a face line corresponding to the face image from a target database based on the face image, and using the face line corresponding to the face image as a standard face line of the target user;

[0035] In response to the fact that the facial line corresponding to the facial image does not exist in the target database, the standard facial line of the target user is obtained according to the following steps: in response to detecting the facial image of the target user in the target screen, a first display interface is displayed, wherein the first display interface includes the facial image and a facial line drawing control; in response to detecting that the target user performs a facial line drawing operation on the facial image through the facial line drawing control in the first display interface, the standard facial line of the target user is generated according to the facial line drawing operation.

[0036] Specifically, the first display interface is used to enable the user to draw a standard face through user interaction. As a reference, the first display interface may further include the line where the chin of the target user is sitting upright as a reference face standard line.

[0037] The standard sitting posture is initialized by the user manually drawing a line, which makes it simple and accurate to obtain the standard sitting posture. When the height of the chair or desk changes, it is convenient for the user to adjust the standard sitting posture in time.

[0038] Step 102 : In response to detecting the face image of the target user in the target image, extracting face information from the face image to obtain face information.

[0039] In some embodiments, in response to detecting the facial image of the target user in the target screen, the execution entity (eg, electronic device) may extract facial information from the facial image to obtain facial information.

[0040] Specifically, the facial image generally refers to a set of image frames containing the user's face. As an example, the facial image may also be a set of image frames in which the user's face moves into the camera image. As another example, the facial image may also be a set of image frames in which the user's face leaves the camera image. The target image generally refers to a camera image of the user for whom sitting posture detection is required. As an example, the target image may be a surveillance video. As another example, the target image may also be a video or image of the target user captured by the electronic device via a camera or other means.

[0041] Here, the facial information generally refers to information about key points of the face, head pose information, and the coordinates of the bounding box of the face in the image. As an example, the facial information may include the location of organs such as the nose, eyes, and mouth. As another example, the facial information may also include the tilt angle of the face.

[0042] In some optional implementations of some embodiments, the above-mentioned execution entity may input the above-mentioned facial image into a pre-trained face detection model to obtain the above-mentioned facial information, wherein the above-mentioned face detection model is obtained by training the above-mentioned initial model with the YOLOV5 model as the initial model, the sample facial image as the input, and the sample facial information corresponding to the sample facial image as the expected output.

[0043] Step 103: Determine the sitting posture information of the target user based on the standard facial line and the facial information.

[0044] In some embodiments, the execution entity may determine the sitting posture information of the target user based on the standard facial line and the facial information.

[0045] In some optional implementations of some embodiments, the above-mentioned facial information includes facial frame information, facial key point information and head posture information, and the above-mentioned standard facial line includes standard facial frame information and standard head posture information.

[0046] In response to determining that the difference between the coordinate value of the lower edge of the face frame and the coordinate value of the lower edge of the standard face frame exceeds a preset threshold, determining that the sitting posture information of the target user is a non-standard sitting posture;

[0047] determining a head posture change angle of the target user based on the standard head posture information and the head posture information; and determining that the sitting posture information of the target user is a non-standard sitting posture in response to determining that the head posture change angle exceeds a preset angle;

[0048] In response to determining that the difference between the coordinate value of the lower edge of the face frame and the coordinate value of the lower edge of the standard face frame does not exceed a preset threshold, the sitting posture information of the target user is determined to be a standard sitting posture.

[0049] Specifically, the execution entity may determine the user's sitting posture information by comparing the standard facial line with the facial information.

[0050] Here, the above-mentioned sitting posture information generally refers to whether the user's sitting posture deviates from the standard facial line.

[0051] Here, facial key points generally refer to 25 key points including eyebrows, eyes, nose, and mouth. As an example, the above execution entity can obtain facial key point information by extracting the face image obtained by face detection from the original image, inputting it into the facial key point detection model, and the model outputting the facial key points.

[0052] The head pose information mentioned above usually refers to the three angles of the face, namely pitch, yaw, and roll. Face spatial angles: pitch refers to the rotation angle of the head around the y-axis, yaw refers to the rotation angle of the head around the z-axis, and roll refers to the rotation angle of the head around the x-axis.

[0053] As an example, the above-mentioned execution subject can obtain the head posture information in the following way: extract the face image obtained by detection from the original image, input it into the basic model of the head posture estimation model, and the model outputs the face spatial angle.

[0054] In some optional implementations of some embodiments, the above method also includes: in response to detecting that the target user leaves the above target screen, obtaining a face image set before the target user leaves the above target screen; determining the head posture change angle, face movement direction and face movement distance of the above target user based on the face images in the above face image set; in response to determining that the above face movement direction and the above head posture change angle are downward, and the above face movement distance exceeds a preset threshold, determining that the sitting posture information of the above target user is a non-standard sitting posture; in response to determining that the above face movement direction and the above head posture change angle are upward, and the above face movement distance exceeds a preset threshold, determining that the sitting posture information of the above target user is a non-standard sitting posture.

[0055] Specifically, the execution entity can detect whether there is a face in the current image and determine whether the face has disappeared. If there is no face in the current image, it is necessary to determine whether the face has disappeared due to the subject being out of frame or due to an incorrect sitting posture. This determination is primarily based on changes in the face frame coordinates and head posture angle values across consecutive frames. When the subject lowers their head until their face is no longer detectable, the lower edge of the face frame continuously moves downward, and the head posture angle value increases downward. When the subject raises their head until their face is no longer detectable, the lower edge of the face frame continuously moves upward, and the head posture angle value increases upward. Based on the movement direction of the face frame's lower edge and changes in head posture angle across multiple frames before the face disappears, it can be determined whether the face was not detected due to an incorrect sitting posture. In this case, the sitting posture should be considered incorrect. If neither of these conditions is met, the subject is deemed to have disappeared from the image, and sitting posture detection is not performed.

[0056] Step 104: Generate target prompt information according to the sitting posture information and send the target prompt information to the target user device.

[0057] In some embodiments, the execution entity may generate target prompt information according to the sitting posture information and send the target prompt information to the target user device.

[0058] Here, the target prompt information generally refers to prompt information generated based on the user's sitting posture information. As an example, the target prompt information may be information used to prompt the user to sit properly. As another example, the target prompt information may also be information used to remind the user not to sit for a long time.

[0059] In some optional implementations of some embodiments, in response to determining that the sitting posture information is a non-standard sitting posture, generating sitting posture prompt information as target prompt information and sending the target prompt information to the target user device; or

[0060] In response to determining that the sitting posture information is a standard sitting posture and the target user maintains the standard sitting posture for a period exceeding a preset threshold, sedentary prompt information is generated as target prompt information and the target prompt information is sent to the target user device.

[0061] By analyzing the disappearance of the target, it can alarm when the face disappears due to incorrect sitting posture, and not alarm when the target walks out of the screen, thereby improving the accuracy of sitting posture detection and avoiding missed reports due to failure to detect the face.

[0062] As an example, a method for sitting posture detection can be implemented by the following steps:

[0063] Step 1: The user draws a standard face reference and selects the chin of the target when sitting upright as the standard face line.

[0064] Step 2: Face information extraction, mainly using the face detection model to extract the user's face frame coordinates (x, y, w, h), face key points (25 points) and head posture (pitch, yaw, row).

[0065] Where x is the x-axis coordinate of the upper left corner of the face frame, y is the y-axis coordinate of the upper left corner of the face frame, w is the width of the face frame, and h is the height of the face frame. Head pose pitch represents the rotation angle of the object around the x-axis, yaw represents the rotation angle of the object around the y-axis, and row represents the rotation angle of the object around the z-axis.

[0066] Step 3: Detect whether there is a face in the current image and determine if the face disappears.

[0067] If there's no face in the current frame, we need to determine whether the face's disappearance is due to the subject being out of frame or due to an incorrect sitting posture. This determination is primarily based on changes in the face frame coordinates and head posture angle values across consecutive frames. When the subject lowers their head until their face is no longer detectable, the lower edge of the face frame continuously moves downward, and the head posture angle value increases downward. When the subject raises their head until their face is no longer detectable, the lower edge of the face frame continuously moves upward, and the head posture angle value increases upward. Based on the movement direction of the face frame's lower edge and changes in head posture angle across multiple frames before the face disappears, we can determine whether the face's disappearance is due to incorrect sitting posture. In this case, the posture should be considered incorrect. If neither of these conditions is met, the subject is considered to have disappeared from the frame, and sitting posture detection is not performed.

[0068] Step 4: Determine the number of targets in the current image. If the number of targets in the current image is greater than 1, do not perform sitting posture detection. If the number of targets in the current image is 1, perform sitting posture detection on the target. The main basis is:

[0069] 1. When the y-value of the lower edge of the face frame exceeds the y-value of the face standard line plus 0.65 times the face height, the sitting posture is considered non-standard, that is, y>y0+0.65*h; where y is the y-value of the lower edge of the face frame, y0 is the y-value of the face standard line, and h is the height of the face frame.

[0070] 2. When the angle of raising and lowering the head is greater than 40°, the sitting posture is considered to be non-standard.

[0071] According to the above two standards, the sitting posture of the target in the picture can be judged, and the sitting posture result can be saved in the sitting posture result queue. When the sitting posture in the queue meets the non-standard sitting posture number of more than 40 frames in 50 frames, the user will be given an alarm reminder for non-standard sitting posture.

[0072] Step 5: When the target is sitting in the correct posture, the average value of the facial key points is calculated and compared with the average value of the facial key points in the previous frame. If the average coordinate change of the facial key points in adjacent frames is small and does not exceed the set threshold, it is considered that the target has not moved significantly. At this time, the sedentary reminder counter is increased by 1, and it is judged whether the sedentary reminder counter exceeds the threshold. If it exceeds the threshold, the target is reminded to sit for a long time; if the coordinate change of adjacent frames is large and exceeds the set threshold, it is considered that the target has moved significantly, and the sedentary reminder counter is cleared.

[0073] As another example, the method for sitting posture detection can also be performed as follows: Figure 2 The sitting posture detection flowchart shown is implemented.

[0074] One of the above-mentioned embodiments of the present disclosure has the following beneficial effects: by using the user to draw a line to determine the standard sitting posture, an accurate standard sitting posture can be quickly obtained, thereby improving the accuracy of determining the standard sitting posture. Two situations where there is no face in the picture are analyzed: the disappearance of the face due to a non-standard sitting posture and the target being out of the frame. An abnormal sitting posture alarm is triggered when the face disappears due to a non-standard sitting posture, while no abnormal sitting posture alarm is triggered when the target is out of the frame. By analyzing the disappearance of the face, missed reports are reduced, the accuracy of the algorithm is improved, and a correct sitting posture alarm can be triggered, thereby improving the accuracy of sitting posture detection.

[0075] Further references Figure 3 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a device for sitting posture detection. These device embodiments are similar to Figure 1Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.

[0076] like Figure 3 As shown, some embodiments of the apparatus 300 for sitting posture detection include: an acquisition unit 301, an extraction unit 302, a determination unit 303, and a generation unit 304. The acquisition unit 301 is configured to acquire a standard facial line of a target user; the extraction unit 302 is configured to, in response to detecting a facial image of the target user in a target image, extract facial information from the facial image to obtain facial information; the determination unit 303 is configured to determine the sitting posture information of the target user based on the standard facial line and the facial information; and the generation unit 304 is configured to generate target prompt information based on the sitting posture information and send the target prompt information to the target user device.

[0077] It is understood that the units described in the device 300 are similar to those in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the device 300 and the units included therein, and will not be repeated here.

[0078] One of the above-mentioned embodiments of the present disclosure has the following beneficial effects: by using the user to draw a line to determine the standard sitting posture, an accurate standard sitting posture can be quickly obtained, thereby improving the accuracy of determining the standard sitting posture. Two situations where there is no face in the picture are analyzed: the disappearance of the face due to a non-standard sitting posture and the target being out of the frame. An abnormal sitting posture alarm is triggered when the face disappears due to a non-standard sitting posture, while no abnormal sitting posture alarm is triggered when the target is out of the frame. By analyzing the disappearance of the face, missed reports are reduced, the accuracy of the algorithm is improved, and a correct sitting posture alarm can be triggered, thereby improving the accuracy of sitting posture detection.

[0079] Reference below Figure 4 , which shows an electronic device (eg, Figure 1 A structural diagram of the electronic device 400. Figure 4 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0080] like Figure 4As shown, the electronic device 400 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 408 into a random access memory (RAM) 403. Various programs and data required for the operation of the electronic device 400 are also stored in the RAM 403. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0081] Typically, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 may allow the electronic device 400 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The electronic device 400 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead. Figure 4 Each block shown in the figure may represent one device, or may represent multiple devices as needed.

[0082] In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from a network via the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of some embodiments of the present disclosure are performed.

[0083] It should be noted that the computer-readable medium described above in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0084] In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. Furthermore, in some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0085] A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0086] In some embodiments, the client and server can communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0087] The computer-readable medium may be included in the electronic device, or may exist independently and not incorporated into the electronic device. The computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: obtain a target user's standard facial line; in response to detecting a facial image of the target user in a target screen, extract facial information from the facial image to obtain facial information; determine the target user's sitting posture information based on the standard facial line and the facial information; generate target prompt information based on the sitting posture information, and transmit the target prompt information to the target user's device.

[0088] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0089] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0090] The units described in some embodiments of the present disclosure may be implemented via software or hardware. The units described may also be provided within a processor. For example, they may be described as comprising an acquisition unit, an extraction unit, a determination unit, and a generation unit. The names of these units do not, in some cases, limit the units themselves. For example, the acquisition unit may also be described as a "unit for acquiring the standard facial lines of a target user."

[0091] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0092] Some embodiments of the present disclosure further provide a computer program product, including a computer program, which implements any of the above-mentioned methods for sitting posture detection when executed by a processor.

[0093] The above description is only an illustration of some preferred embodiments of the present disclosure and the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A method for sitting posture detection, comprising: Obtain the target user's standard facial line; In response to detecting a face image of the target user in the target picture, extracting face information from the face image to obtain face information; determining the sitting posture information of the target user according to the standard face line and the face information; Target prompt information is generated according to the sitting posture information and the target prompt information is sent to a target user device.

2. The method according to claim 1, wherein The step of obtaining the target user's standard facial line includes: In response to detecting a face image of the target user in a target picture, obtaining a face line corresponding to the face image from a target database according to the face image, and using the face line corresponding to the face image as a standard face line of the target user; In response to the fact that a facial line corresponding to the facial image does not exist in the target database, the standard facial line of the target user is obtained according to the following steps: in response to detecting the facial image of the target user in the target screen, a first display interface is displayed, wherein the first display interface includes the facial image and a facial line drawing control; in response to detecting that the target user performs a facial line drawing operation on the facial image through the facial line drawing control in the first display interface, the standard facial line of the target user is generated according to the facial line drawing operation.

3. The method according to claim 1, wherein The extracting facial information from the facial image to obtain facial information includes: The face image is input into a pre-trained face detection model to obtain the face information, wherein the face detection model is obtained by training the initial model with the YOLOV5 model as the initial model, the sample face image as the input, and the sample face information corresponding to the sample face image as the expected output.

4. The method according to claim 1, wherein The facial information includes facial frame information, facial key point information, and head posture information; the standard facial line includes standard facial frame information and standard head posture information; and determining the sitting posture information of the target user based on the standard facial line and the facial information includes: In response to determining that the difference between the coordinate value of the lower edge of the face frame and the coordinate value of the lower edge of the standard face frame exceeds a preset threshold, determining that the sitting posture information of the target user is a non-standard sitting posture; determining a head posture change angle of the target user based on the standard head posture information and the head posture information; and determining that the sitting posture information of the target user is a non-standard sitting posture in response to determining that the head posture change angle exceeds a preset angle; In response to determining that the difference between the lower edge coordinate value of the face frame and the lower edge coordinate value of the standard face frame does not exceed a preset threshold, it is determined that the sitting posture information of the target user is a standard sitting posture.

5. The method according to claim 1, wherein The method further comprises: In response to detecting that the target user leaves the target screen, acquiring a face image set of the target user before leaving the target screen; Determining the head posture change angle, face movement direction, and face movement distance of the target user based on the face images in the face image set; In response to determining that the face movement direction and the head posture change angle are downward, and the face movement distance exceeds a preset threshold, determining that the sitting posture information of the target user is a non-standard sitting posture; In response to determining that the face movement direction and the head posture change angle are upward, and the face movement distance exceeds a preset threshold, it is determined that the sitting posture information of the target user is a non-standard sitting posture.

6. The method according to claim 1, wherein The generating target prompt information according to the sitting posture information and sending the target prompt information to the target user device includes: In response to determining that the sitting posture information is a non-standard sitting posture, generating sitting posture prompt information as target prompt information and sending the target prompt information to the target user device; or In response to determining that the sitting posture information is a standard sitting posture and the target user maintains the standard sitting posture for a period exceeding a preset threshold, sedentary prompt information is generated as target prompt information and the target prompt information is sent to the target user device.

7. A device for detecting sitting posture, comprising: an acquisition unit configured to acquire a standard facial line of a target user; an extraction unit configured to, in response to detecting a face image of the target user in the target picture, extract face information from the face image to obtain face information; a determining unit configured to determine the sitting posture information of the target user based on the standard face line and the face information; The generating unit is configured to generate target prompt information according to the sitting posture information and send the target prompt information to a target user device.

8. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method for sitting posture detection as described in any one of claims 1 to 6.

9. A computer-readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method for sitting posture detection as described in any one of claims 1 to 6 can be implemented.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program can implement the method for sitting posture detection according to any one of claims 1 to 6.

Images