WO2023123213A1 - Hand pressing depth measurement method and apparatus - Google Patents

Hand pressing depth measurement method and apparatus Download PDF

Info

Publication number
WO2023123213A1
WO2023123213A1 PCT/CN2021/143103 CN2021143103W WO2023123213A1 WO 2023123213 A1 WO2023123213 A1 WO 2023123213A1 CN 2021143103 W CN2021143103 W CN 2021143103W WO 2023123213 A1 WO2023123213 A1 WO 2023123213A1
Authority
WO
WIPO (PCT)
Prior art keywords
marker
target
target color
hand
video
Prior art date
Application number
PCT/CN2021/143103
Other languages
French (fr)
Chinese (zh)
Inventor
焦旭
Original Assignee
焦旭
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 焦旭 filed Critical 焦旭
Priority to PCT/CN2021/143103 priority Critical patent/WO2023123213A1/en
Priority to CN202180005746.XA priority patent/CN114556447A/en
Publication of WO2023123213A1 publication Critical patent/WO2023123213A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]

Definitions

  • the invention belongs to the technical field of image processing, and in particular relates to a hand pressing depth detection method and detection device, a computer-readable medium and electronic equipment.
  • the present invention proposes a hand pressing depth detection method, comprising the following steps:
  • the target video is a video captured by a fixed shooting device for the pressing action of the hand, and the hand is worn with a marker;
  • the pressing depth of the hand is obtained.
  • the coordinates of the highest point are the coordinates of the upper edge of the marker when the marker is at the highest point
  • the coordinates of the lowest point are the coordinates of the marker when the marker is at the lowest point.
  • the coordinates of the lower edge are the coordinates of the upper edge of the marker when the marker is at the highest point.
  • the step of performing marker detection on the target video includes:
  • Converting the video frame image to the HSV color space, in the HSV color space, according to the target color perform binarization processing, segment the video frame image, and obtain the target color image;
  • N convolution kernels to convolve the target color image respectively, and add the outputs of each convolution kernel, and count the point with the largest kernel function response, and whether the area where the point with the largest statistical response is located is greater than the threshold, if it is greater than the threshold , determine that there is a target, and set a tracking frame according to the area of the target color image, where N is an integer greater than or equal to 3.
  • the first target color and the second target color are spaced apart from each other on the marker, and the target color image includes the first target color image and the second target color image; before performing convolution processing, it also includes, Dilation processing and erosion processing are performed on the second target color image, and an intersection operation is performed on the first target color image.
  • setting the tracking frame according to the area of the target color image includes: setting the tracking frame according to the union area of the first target color image and the second target color image.
  • the first target color is white
  • the second target color is green
  • the step of tracking the markers includes: tracking the markers using KCF algorithm.
  • the detection method further includes, judging that the hand pressing depth information satisfies a pressing threshold, and displaying prompt information.
  • an embodiment of the present invention provides a hand pressing depth detection device, including:
  • the reading module is used to read the target video, the target video is a video captured by the fixed shooting device for the pressing action of the hand, and the hand is worn with a marker;
  • a detection module configured to perform marker detection on the target video, and obtain a tracking frame of the marker
  • a tracking module which tracks the tracking frame and obtains the highest point and the lowest point of the marker in the pressing direction;
  • the ranging module is configured to obtain the hand pressing depth according to the coordinates of the highest point and the lowest point.
  • an electronic device including:
  • processors one or more processors
  • the one or more processors When the one or more programs are executed by the one or more processors, the one or more processors implement any one of the methods described above.
  • a fourth aspect of the present invention provides a computer-readable medium on which a computer program is stored, wherein when the program is executed by a processor, any one of the above-mentioned methods is implemented.
  • the invention provides a method for measuring distance by using image information. Firstly, marker detection is performed, and then tracking is performed to obtain the position of the highest point and the lowest point, and the pressed distance information is obtained according to the difference between the positions of the highest point and the lowest point.
  • the square video information in the embodiment of the present invention can be collected by a monocular camera device, for example, by a mobile phone, which reduces the performance requirements of the device used. Through the detection of compression depth information, it can quickly judge whether the compression depth reaches the standard, thereby improving the quality of CPR.
  • Fig. 1 is a schematic diagram of the system architecture of the hand pressing depth detection method and detection device operation in some examples of the present invention
  • Fig. 2 is a schematic flow chart of a hand pressing depth detection method in some examples of the present invention.
  • FIG. 3 is a schematic diagram of a video shot in a hand pressing depth detection method in some embodiments of the present invention.
  • Fig. 4 is a schematic flow chart of detecting markers in the hand pressing depth detection method in some embodiments of the present invention.
  • Fig. 5 is a schematic flow chart of detecting markers in the hand pressing depth detection method in some embodiments of the present invention.
  • Fig. 6 is a schematic flow chart of the tracking steps in the hand pressing depth detection method in some embodiments of the present invention.
  • Fig. 7 is a schematic flowchart of a hand pressing depth detection method in other embodiments of the present invention.
  • Fig. 8 is a system schematic diagram of a detection device implemented based on the detection method in the above-mentioned drawings in some embodiments of the present invention.
  • Fig. 9 is a schematic structural diagram of a computer system in which a hand pressing depth detection method or a detection device operates in some embodiments of the present invention.
  • Fig. 1 shows an exemplary system architecture 100 to which the embodiment of the hand pressing depth detection method or detection device according to the embodiment of the present application can be applied.
  • a system architecture 100 may include terminal devices 101 , 102 , 103 , a network 104 and a server 105 .
  • the network 104 is used as a medium for providing communication links between the terminal devices 101 , 102 , 103 and the server 105 .
  • Network 104 may include various connection types, such as wires, wireless communication links, or fiber optic cables, among others.
  • Terminal devices 101 , 102 , 103 Users can use terminal devices 101 , 102 , 103 to interact with server 105 via network 104 to receive or send data (such as video) and the like.
  • Various communication client applications can be installed on the terminal devices 101, 102, 103, such as video playback software, video processing applications, web browser applications, shopping applications, search applications, instant messaging tools, email clients, social networking platform software, etc.
  • the terminal devices 101, 102, and 103 may be hardware or software.
  • the terminal devices 101, 102, 103 When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices with display screens and supporting data transmission, including but not limited to smart phones, tablet computers, laptop computers and desktop computers, etc.
  • the terminal devices 101, 102, 103 When the terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules (such as software or software modules for providing distributed services), or as a single software or software module. No specific limitation is made here.
  • the server 105 may be a server that provides various services, such as a background server that provides support for videos displayed on the terminal devices 101 , 102 , 103 .
  • the background server can analyze and process the received data such as slicing requests, and feed back the processing results (such as indexed slices or slicing sequences) to electronic devices (such as terminal devices) connected in communication with it.
  • the hand pressing depth detection method provided in the embodiment of the present application can be executed by the server 105 , and correspondingly, the pressing depth detection device can be set in the server 105 .
  • the hand pressing depth detection method provided in the embodiment of the present application can also be executed by the terminal devices 101, 102, 103, and accordingly, the hand pressing depth detection device can also be set in the terminal devices 101, 102, 103.
  • the server may be hardware or software.
  • the server can be implemented as a distributed server cluster composed of multiple servers, or as a single server.
  • the server is software, it can be implemented as multiple software or software modules (such as software or software modules for providing distributed services), or as a single software or software module. No specific limitation is made here.
  • the numbers of terminal devices, networks and servers in Fig. 1 are only illustrative. According to the implementation needs, there can be any number of terminal devices, networks and servers.
  • the system architecture may only include the electronic devices on which the hand pressing depth detection method runs (such as terminal devices 101, 102, 103 or server 105).
  • the embodiment of the present invention obtains the position information of the highest point and the lowest point through the visual tracking technology, and then obtains the compression depth through the difference of the position information, so that the detection efficiency and accuracy are effectively guaranteed.
  • the front CCD camera equipped with the mobile phone is used to shoot the pressing action, and after digital image processing, the pressing depth information is measured and obtained.
  • the embodiment of the present invention adopts the idea of combining the traditional scale measurement, extracts the wristband when pressed through digital image processing, and completes the distance measurement with guaranteed speed and accuracy through the vertical distance of the movement of the wristband through algorithm-assisted calculation.
  • the overall scheme is shown in Figure 2.
  • the front pressing action is captured by the front camera of the mobile phone, as shown in Figure 3. Process the captured video into an image sequence. In order to ensure the speed of distance measurement, it is necessary to detect and track the target through the captured image, detect the specific position at the highest point of the press and the highest point, and complete the distance measurement. Assuming that the target is a bracelet, then detect the bracelet from a series of images to obtain the position of the bracelet in each image in the image coordinates, and determine the position of the bracelet with the highest point of coordinates and the lowest point of coordinates, and the obtained position The distance between them is the compression depth.
  • the embodiment of the present invention uses the KCF algorithm to track the target, track the movement of the wrist and record the coordinate information of the target frame. The extreme point in the motion process is extracted through the recorded data, and the picture of the frame is input into the distance measurement module to complete the final distance measurement. Judge whether the compression depth of 5cm is reached, and display it in the video in real time.
  • the detection method includes the following steps:
  • the bracelet Since the bracelet is selected as a bracelet structure with green and white spaced apart from each other, the color features are obvious. Therefore, the image is converted to the HSV color space to facilitate color screening and extraction. The hue and brightness of its color are directly selected as the threshold, and the target segmentation and detection are realized through binarization.
  • the HSV space model and other color spaces are represented by circles through the H dimension.
  • the delineated target should be selected as large as possible. Therefore, further, the embodiment of the present invention selects the union of white and green areas to ensure a large target, and returns the tracking frame [x, y, H, W].
  • the embodiment of the present invention proposes a method using a correlation kernel operation, which can ensure a good tracking effect when the target is only slightly deformed and moves fast, and can effectively extract the trajectory of the target moving up and down.
  • the flow of the KCF algorithm is shown in Figure 6.
  • the steps to be executed include a pre-computation, b training and updating the model, and c finding the target position; first execute step a, then execute step b for the first frame of image, and for the image after the second frame image, loop through steps c and b.
  • the measure of the similarity value of two signals is measured by correlation. If the two signals are more similar, the higher the correlation value is.
  • the filter template is used to maximize the response when it acts on the tracking target.
  • the location of the maximum response value is the location of the target.
  • KCF Simple implementation, good effect and fast speed. A large number of samples are generated by cyclic matrix displacement to solve the problem, and the calculation speed in the frequency domain is extremely fast through the derivation of the discrete Fourier transform. In the case of lack of samples, it is detected by a simple method, and the core operation is connected to track, which ensures the generalization ability of the track. Using the KCF algorithm has the following advantages.
  • Kernel regression speed up For the kernel function, it can also be converted to the frequency domain for training and detection, greatly improving the speed
  • the special kernel function is further accelerated: for the Gaussian kernel, the polynomial kernel can further use the circulant matrix to calculate the circulant matrix of the kernel function
  • Tracking can quickly track the experimental goals. By inputting the video of manual pressing into the program, the distance it moves can be displayed stably.
  • the target moves fast, and the distance is small and the accuracy is high. Therefore, in order to ensure the ranging module, it is necessary to improve the reference system.
  • the following factors need to be considered in the detection distance:
  • the pixel of the camera itself may cause a loss of precision, and the error E can be obtained by the following formula.
  • the embodiments of the present invention can use low-cost equipment to implement distance measurement through the marker tracking method, thereby reducing equipment requirements. It overcomes the shortcomings of the traditional monocular ranging method that requires a fixed reference object, has low precision, and cannot adapt to long-distance measurement occasions.
  • FIG. 7 another embodiment of the present invention provides a mobile phone pressing depth detection method, including the following steps:
  • the target video is a video captured by a fixed shooting device for the pressing action of a hand, and a marker is worn on the hand.
  • a marker is worn on the hand.
  • the subject to be pressed lies flat on the ground, the position of the shooting equipment is almost at the same height as the pressing position, and the video is shot and recorded from the side of the pressing action.
  • S22 Perform marker detection on the target video, and obtain the tracking frame of the marker; specifically, generate a sequence of video frames from the target video in chronological order; convert the video frame images into HSV color space, and In the HSV color space, according to the target color, binarization processing is performed, the video frame image is segmented, and the target color image is obtained; N convolution kernels are used to convolve the target color image respectively, and each convolution kernel The output is added together, the point with the largest statistical kernel function response, whether the area where the point with the largest statistical response is located is greater than the threshold value, if greater than the threshold value, it is judged that there is a target, and the tracking frame is set according to the area of the target color image, where N is greater than An integer equal to 3.
  • the first target color and the second target color are spaced apart from each other on the marker, and the target color image includes the first target color image and the second target color image; before performing convolution processing, it also includes, Dilation processing and erosion processing are performed on the second target color image, and an intersection operation is performed on the first target color image.
  • setting the tracking frame according to the area of the target color image includes: setting the tracking frame according to the union area of the first target color image and the second target color image.
  • the first target color is white, and the second target color is green.
  • the color contrast is obvious, which is good for detection.
  • the coordinates of the highest point are the coordinates of the upper edge of the marker when the marker is at the highest point
  • the coordinates of the lowest point is the coordinate of the lower edge of the marker when the marker is at the lowest point.
  • the detection method further includes, S25, judging that the hand pressing depth information satisfies the pressing threshold, and displaying prompt information. For example, if the compression depth meets the compression threshold, it will display qualified, or display green.
  • the hand pressing depth detection method in the embodiment of the present invention obtains the pressing depth by using the coordinates of the uppermost edge at the highest point and the coordinates of the lowermost edge at the lowest point, fully considering the measurement error and ensuring the accuracy of the measurement.
  • the measurement by the tracking method reduces the performance requirement of the ranging equipment and reduces the cost of method implementation.
  • the embodiment of the present invention also provides a hand pressing depth detection device 300, including:
  • the reading module 310 is used to read the target video, the target video is a video captured by the fixed shooting device for the pressing action of the hand, and the hand is worn with a marker;
  • a detection module 320 configured to perform marker detection on the target video, and obtain a tracking frame of the marker
  • the tracking module 330 is configured to track the tracking frame, and obtain the highest point and the lowest point of the marker in the pressing direction;
  • the ranging module 340 is configured to obtain the hand pressing depth according to the coordinates of the highest point and the lowest point.
  • FIG. 9 shows a schematic structural diagram of a computer system 800 suitable for implementing the control device of the embodiment of the present application.
  • the control device shown in FIG. 9 is only an example, and should not limit the functions and scope of use of this embodiment of the present application.
  • a computer system 800 includes a central processing unit (CPU) 801 that can be programmed according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage section 808 into a random-access memory (RAM) 803 Instead, various appropriate actions and processes are performed.
  • ROM read-only memory
  • RAM random-access memory
  • various programs and data required for the operation of the system 800 are also stored.
  • the CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804.
  • An input/output (I/O) interface 805 is also connected to the bus 804 .
  • the following components are connected to the I/O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 808 including a hard disk, etc. and a communication section 809 including a network interface card such as a LAN card, a modem, or the like.
  • the communication section 809 performs communication processing via a network such as the Internet.
  • a drive 810 is also connected to the I/O interface 805 as needed.
  • a removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 810 as necessary so that a computer program read therefrom is installed into the storage section 808 as necessary.
  • embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, where the computer program includes program codes for executing the methods shown in the flowcharts.
  • the computer program may be downloaded and installed from a network via communication portion 809 and/or installed from removable media 811 .
  • the central processing unit (CPU) 801 the above-mentioned functions defined in the method of the present application are performed.
  • the computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two.
  • a computer readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable Programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, in which computer-readable program codes are carried. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • a computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.
  • Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
  • Computer program code for carrying out the operations of this application can be written in one or more programming languages, or combinations thereof, including object-oriented programming languages—such as Python, Java, Smalltalk, C++, and Includes conventional procedural programming languages - such as the "C" language or similar programming languages.
  • the program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server.
  • the remote computer can be connected to the user computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as through an Internet service provider). Internet connection).
  • each block in a flowchart or block diagram may represent a module, program segment, or portion of code that contains one or more logical functions for implementing specified executable instructions.
  • the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved.
  • each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations can be implemented by a dedicated hardware-based system that performs the specified functions or operations , or may be implemented by a combination of dedicated hardware and computer instructions.
  • the units involved in the embodiments described in the present application may be implemented by means of software or by means of hardware.
  • the described units may also be set in a processor, for example, it may be described as: a processor includes an acquiring unit, a dividing unit, a determining unit and a selecting unit. Wherein, the names of these units do not constitute a limitation on the unit itself under certain circumstances, for example, the acquisition unit may also be described as "a unit for acquiring picture book images to be processed".
  • the present application also provides a computer-readable medium.
  • the computer-readable medium may be included in the electronic device described in the above embodiments; it may also exist independently without being assembled into the electronic device. middle.
  • the above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device: reads the target video, and the target video is pressed by the fixed shooting device against the hand Actions are collected to obtain the video, and the hands are worn with markers; marker detection is performed on the target video, and the tracking frame of the marker is acquired; the tracking frame is tracked, and the marker is acquired The highest point and the lowest point in the pressing direction; according to the coordinates of the highest point and the lowest point, the pressing depth of the hand is obtained.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • Computing Systems (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Image Analysis (AREA)

Abstract

A hand pressing depth measurement method, comprising the following steps: reading a target video, the target video being a video acquired by a fixed photographing device for a hand pressing action, and a marker being worn on a hand (S21); performing marker detection on the target video to obtain a tracking frame of the marker (S22); tracking the tracking frame to obtain a highest point and a lowest point of the marker in a pressing direction (S23); and obtaining a hand pressing depth according to coordinates of the highest point and coordinates of the lowest point (S24). The problems of complex structure, high cost and low accuracy of a non-contact measurement device are solved. Moreover, a corresponding apparatus, a device, and a medium are provided.

Description

手部按压深度检测方法及装置Hand pressing depth detection method and device 技术领域technical field
本发明属于图像处理技术领域，具体而言，涉及一种手部按压深度检测方法及检测装置、计算机可读介质及电子设备。The invention belongs to the technical field of image processing, and in particular relates to a hand pressing depth detection method and detection device, a computer-readable medium and electronic equipment.
背景技术Background technique
据估计，加拿大和美国每年共有33万例院外心脏骤停(OHCA)导致的死亡。在治疗的OHCA中，总体生存率很低，出院率从3.0％到16.3％不等。患者生存率率的差异可部分归因于下列5个重要环节：快速紧急医疗***(ENS)通道；早期心肺复苏(CPR)；早期除颤；早期高级生命支持(ACLS)；有效的复苏后治疗。近些年，在社区和医院大力加强上述环节后，生存率也只得到轻微的提高。近年来，人们已经认识到心脏复苏中CPR的质量、次数和及时性对心脏骤停患者的生存至关重要。相关的研究发现，CPR时按压深度的增加与生存率改善的程度密切相关，而当按压深度为4.03-5.53cm(峰值4.56cm)时，患者的生存率最高。但是在实际的心脏复苏的过程中，由于缺乏测量深度的工具，很难评价心脏复苏中的按压深度。传统的接触式测量测距精度高、稳定性好，但由于受到体积、质量、安装条件、结构以及操作不方便等因素影响而得不到广泛利用；在实际情况中也很难实现在按压者和患者身上通过接触性的仪器进行测距。An estimated 330,000 deaths from out-of-hospital cardiac arrest (OHCA) occur each year in Canada and the United States. In treated OHCA, overall survival is poor, with discharge rates ranging from 3.0% to 16.3%. The difference in patient survival rates can be attributed in part to the following five important components: rapid emergency medical system (ENS) access; early cardiopulmonary resuscitation (CPR); early defibrillation; early advanced life support (ACLS); effective post-resuscitative care . In recent years, after the communities and hospitals have vigorously strengthened the above-mentioned links, the survival rate has only slightly improved. In recent years, it has been recognized that the quality, frequency, and timeliness of CPR during cardiac resuscitation are critical to survival in cardiac arrest. Related studies have found that the increase in compression depth during CPR is closely related to the degree of improvement in survival rate, and when the compression depth is 4.03-5.53cm (peak value 4.56cm), the patient's survival rate is the highest. However, in the actual process of cardiac resuscitation, it is difficult to evaluate the compression depth in cardiac resuscitation due to the lack of tools for measuring depth. The traditional contact measurement has high precision and good stability, but it is not widely used due to factors such as volume, quality, installation conditions, structure, and inconvenient operation; Distance measurement is carried out with the patient through contact instruments.
发明内容Contents of the invention
本发明为了解决上述现有技术的缺点，提出了一种手部按压深度检测方法，包括如下步骤：In order to solve the above-mentioned shortcoming of the prior art, the present invention proposes a hand pressing depth detection method, comprising the following steps:
读取目标视频，所述目标视频是由固定拍摄设备针对手部按压动作进行采集获取到的视频，所述手部上佩戴有标志物；Reading the target video, the target video is a video captured by a fixed shooting device for the pressing action of the hand, and the hand is worn with a marker;
对所述目标视频进行标志物检测，获取所述标志物的跟踪边框；Perform marker detection on the target video, and obtain a tracking frame of the marker;
对所述跟踪边框进行跟踪，获取所述标志物在按压方向上的最高点和最低点；Tracking the tracking frame to obtain the highest point and the lowest point of the marker in the pressing direction;
根据所述最高点的坐标和最低点的坐标，获取手部按压深度。According to the coordinates of the highest point and the coordinates of the lowest point, the pressing depth of the hand is obtained.
进一步的，所述最高点的坐标为所述标志物位于最高点时，所述标志物的上边沿的坐标，所述最低点的坐标为所述标志物位于最低点时，所述标志物的下边沿的坐标。Further, the coordinates of the highest point are the coordinates of the upper edge of the marker when the marker is at the highest point, and the coordinates of the lowest point are the coordinates of the marker when the marker is at the lowest point. The coordinates of the lower edge.
进一步的，所述对所述目标视频进行标志物检测的步骤包括：Further, the step of performing marker detection on the target video includes:
将所述目标视频按照时间顺序生成视频帧序列；Generating a sequence of video frames from the target video in chronological order;
将所述视频帧图像转换到HSV颜色空间，在HSV颜色空间中，根据目标颜色，进行二值化处理，分割所述视频帧图像，获取目标颜色图像；Converting the video frame image to the HSV color space, in the HSV color space, according to the target color, perform binarization processing, segment the video frame image, and obtain the target color image;
利用N个卷积核分别对所述目标颜色图像进行卷积，并将各个卷积核的输出相加，统计核函数响应最大的点，统计响应最大的点所在区域是否大于阈值，如果大于阈值，判断存在目标，根据所述目标颜色图像的区域设定跟踪边框，其中，N为大于等于3的整数。Use N convolution kernels to convolve the target color image respectively, and add the outputs of each convolution kernel, and count the point with the largest kernel function response, and whether the area where the point with the largest statistical response is located is greater than the threshold, if it is greater than the threshold , determine that there is a target, and set a tracking frame according to the area of the target color image, where N is an integer greater than or equal to 3.
进一步的，所述标志物上有相互间隔的第一目标颜色和第二目标颜色，所述目标颜色图像包括第一目标颜色图像和第二目标颜色图像；在进行卷积处理之前，还包括，对第二目标颜色图像进行膨胀处理和腐蚀处理，并和所述第一目标颜色图像做交集运算。Further, the first target color and the second target color are spaced apart from each other on the marker, and the target color image includes the first target color image and the second target color image; before performing convolution processing, it also includes, Dilation processing and erosion processing are performed on the second target color image, and an intersection operation is performed on the first target color image.
进一步的，所述根据所述目标颜色图像的区域设定跟踪边框，包括：根据第一目标颜色图像和第二目标颜色图像的并集区域设定所述跟踪边框。Further, setting the tracking frame according to the area of the target color image includes: setting the tracking frame according to the union area of the first target color image and the second target color image.
进一步的，所述第一目标颜色为白色，所述第二目标颜色为绿色。Further, the first target color is white, and the second target color is green.
进一步的，对所述标志物进行跟踪的步骤包括：采用KCF算法对所述标志物进行跟踪。Further, the step of tracking the markers includes: tracking the markers using KCF algorithm.
进一步的，所述检测方法还包括，判断所述手部按压深度信息满足按压阈值，显示提示信息。Further, the detection method further includes, judging that the hand pressing depth information satisfies a pressing threshold, and displaying prompt information.
第二方面，本发明实施例提供了一种手部按压深度检测装置，包括：In the second aspect, an embodiment of the present invention provides a hand pressing depth detection device, including:
读取模块，用于读取目标视频，所述目标视频是由固定拍摄设备针对手部按压动作进行采集获取到的视频，所述手部上佩戴有标志物；The reading module is used to read the target video, the target video is a video captured by the fixed shooting device for the pressing action of the hand, and the hand is worn with a marker;
检测模块，用于对所述目标视频进行标志物检测，获取所述标志物的跟踪边框；A detection module, configured to perform marker detection on the target video, and obtain a tracking frame of the marker;
跟踪模块，对所述跟踪边框进行跟踪，获取所述标志物在按压方向上的最高点和最低点；A tracking module, which tracks the tracking frame and obtains the highest point and the lowest point of the marker in the pressing direction;
测距模块，用于根据所述最高点的坐标和最低点的坐标，获取手部按压深度。The ranging module is configured to obtain the hand pressing depth according to the coordinates of the highest point and the lowest point.
本发明第三方面，提供了一种电子设备，包括：In a third aspect of the present invention, an electronic device is provided, including:
一个或多个处理器；one or more processors;
存储装置，其上存储有一个或多个程序，a storage device on which one or more programs are stored,
当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现上述任一所述的方法。When the one or more programs are executed by the one or more processors, the one or more processors implement any one of the methods described above.
本发明第四方面，提供了一种计算机可读介质，其上存储有计算机程序，其中，所述程序被处理器执行时实现上述任一所述的方法。A fourth aspect of the present invention provides a computer-readable medium on which a computer program is stored, wherein when the program is executed by a processor, any one of the above-mentioned methods is implemented.
本发明提供了一种利用图像信息进行距离测量的方法，首先进行标志物检测，然后进行跟踪，获取到在最高点和最低点的位置，根据最高点和最低点的位置之差获取按压距离信息。特别的，本发明实施例中的方视频信息可以采用单目摄像头设备进行采集，例如可以采用手机进行采集，降低了使用设备的性能要求。通过按压深度信息的检测，能够很快判断按压深度是否达标，从而提升CPR的质量。The invention provides a method for measuring distance by using image information. Firstly, marker detection is performed, and then tracking is performed to obtain the position of the highest point and the lowest point, and the pressed distance information is obtained according to the difference between the positions of the highest point and the lowest point. . In particular, the square video information in the embodiment of the present invention can be collected by a monocular camera device, for example, by a mobile phone, which reduces the performance requirements of the device used. Through the detection of compression depth information, it can quickly judge whether the compression depth reaches the standard, thereby improving the quality of CPR.
附图说明Description of drawings
通过参考附图会更加清楚的理解本发明的特征和优点，附图是示意性的而不应理解为对本发明进行任何限制，在附图中：The features and advantages of the present invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the invention in any way. In the accompanying drawings:
图1为本发明一些实例中的手部按压深度检测方法、检测装置运行的***架构示意图；Fig. 1 is a schematic diagram of the system architecture of the hand pressing depth detection method and detection device operation in some examples of the present invention;
图2为本发明一些实例中的手部按压深度检测方法的流程示意图；Fig. 2 is a schematic flow chart of a hand pressing depth detection method in some examples of the present invention;
图3为本发明一些实施例中的手部按压深度检测方法中拍摄视频的示意图；FIG. 3 is a schematic diagram of a video shot in a hand pressing depth detection method in some embodiments of the present invention;
图4为本发明一些实施例中的手部按压深度检测方法中检测标志物的流程示意图；Fig. 4 is a schematic flow chart of detecting markers in the hand pressing depth detection method in some embodiments of the present invention;
图5为本发明一些实施例中的手部按压深度检测方法中检测标志物的流程示意图；Fig. 5 is a schematic flow chart of detecting markers in the hand pressing depth detection method in some embodiments of the present invention;
图6为本发明一些实施例中的手部按压深度检测方法中跟踪步骤的流程示意图；Fig. 6 is a schematic flow chart of the tracking steps in the hand pressing depth detection method in some embodiments of the present invention;
图7为本发明另一些实施例中的手部按压深度检测方法的流程示意图；Fig. 7 is a schematic flowchart of a hand pressing depth detection method in other embodiments of the present invention;
图8为本发明一些实施例中的基于上述附图中的检测方法所实现的检测装置的***示意图；Fig. 8 is a system schematic diagram of a detection device implemented based on the detection method in the above-mentioned drawings in some embodiments of the present invention;
图9为本发明一些实施例中手部按压深度检测方法或者检测装置运行的计算机***结构示意图。Fig. 9 is a schematic structural diagram of a computer system in which a hand pressing depth detection method or a detection device operates in some embodiments of the present invention.
具体实施方式Detailed ways
为了能够更清楚地理解本发明的上述目的、特征和优点，下面结合附图和具体实施方式对本发明进行进一步的详细描述。需要说明的是，在不冲突的情况下，本申请的实施例及实施例中的特征可以相互组合。In order to understand the above-mentioned purpose, features and advantages of the present invention more clearly, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.
在下面的描述中阐述了很多具体细节以便于充分理解本发明，但是，本发明还可以采用其他不同于在此描述的其他方式来实施，因此，本发明的保护范围并不受下面公开的具体实施例的限制。In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described here. Therefore, the protection scope of the present invention is not limited by the specific details disclosed below. EXAMPLE LIMITATIONS.
图1示出了可以应用本申请实施例的手部按压深度检测方法或检测装置的实施例的示例性***架构100。Fig. 1 shows an exemplary system architecture 100 to which the embodiment of the hand pressing depth detection method or detection device according to the embodiment of the present application can be applied.
如图1所示，***架构100可以包括终端设备101、102、103，网络104和服务器105。网络104用以在终端设备101、102、103和服务器105之间提供通信链路的介质。网络104可以包括各种连接类型，例如有线、无线通信链路或者光纤电缆等等。As shown in FIG. 1 , a system architecture 100 may include terminal devices 101 , 102 , 103 , a network 104 and a server 105 . The network 104 is used as a medium for providing communication links between the terminal devices 101 , 102 , 103 and the server 105 . Network 104 may include various connection types, such as wires, wireless communication links, or fiber optic cables, among others.
用户可以使用终端设备101、102、103通过网络104与服务器105交互，以接收或发送数据(例如视频)等。终端设备101、102、103上可以安装有各种通讯客户端应用，例如视频播放软件、视频处理类应用、网页浏览器应用、购物类应用、搜索类应用、即时通信工具、邮箱客户端、社交平台软件等。Users can use terminal devices 101 , 102 , 103 to interact with server 105 via network 104 to receive or send data (such as video) and the like. Various communication client applications can be installed on the terminal devices 101, 102, 103, such as video playback software, video processing applications, web browser applications, shopping applications, search applications, instant messaging tools, email clients, social networking platform software, etc.
终端设备101、102、103可以是硬件，也可以是软件。当终端设备101、102、103为硬件时，可以是具有显示屏并且支持数据传输的各种电子设备，包括但不限于智能手机、平板电脑、膝上型便携计算机和台式计算机等等。当终端设备101、102、103为软件时，可以安装在上述所列举的电子设备中。其可以实现成多个软件或软件模块(例如用来提供分布式服务的软件或软件模块)，也可以实现成单个软件或软件模块。在此不做具体限定。The terminal devices 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices with display screens and supporting data transmission, including but not limited to smart phones, tablet computers, laptop computers and desktop computers, etc. When the terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules (such as software or software modules for providing distributed services), or as a single software or software module. No specific limitation is made here.
服务器105可以是提供各种服务的服务器，例如对终端设备101、102、103上显示的视频提供支持的后台服务器。后台服务器可以对接收到的切片请求等数据进行分析等处理，并将处理结果(例如索引到的切面或者切片序列)反馈给与其通信连接的电子设备(例如终端设备)。The server 105 may be a server that provides various services, such as a background server that provides support for videos displayed on the terminal devices 101 , 102 , 103 . The background server can analyze and process the received data such as slicing requests, and feed back the processing results (such as indexed slices or slicing sequences) to electronic devices (such as terminal devices) connected in communication with it.
需要说明的是，本申请实施例所提供的手部按压深度检测方法可以由服务器105执行，相应地，按压深度检测装置可以设置于服务器105中。此外，本申请实施例所提供的手部按压深度检测方法也可以由终端设备101、102、103执行，相应地，手部按压深度检测装置也可以设置于终端设备101、102、103中。It should be noted that the hand pressing depth detection method provided in the embodiment of the present application can be executed by the server 105 , and correspondingly, the pressing depth detection device can be set in the server 105 . In addition, the hand pressing depth detection method provided in the embodiment of the present application can also be executed by the terminal devices 101, 102, 103, and accordingly, the hand pressing depth detection device can also be set in the terminal devices 101, 102, 103.
需要说明的是，服务器可以是硬件，也可以是软件。当服务器为硬件时，可以实现成多个服务器组成的分布式服务器集群，也可以实现成单个服务器。当服务器为软件时，可以实现成多个软件或软件模块(例如用来提供分布式服务的软件或软件模块)，也可以实现成单个软件或软件模块。在此不做具体限定。It should be noted that the server may be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster composed of multiple servers, or as a single server. When the server is software, it can be implemented as multiple software or software modules (such as software or software modules for providing distributed services), or as a single software or software module. No specific limitation is made here.
应该理解，图1中的终端设备、网络和服务器的数目仅仅是示意性的。根据实现需要，可以具有任意数目的终端设备、网络和服务器。当直播流播放方法运行于其上的电子设备不需要与其他电子设备进行数据传输时，该***架构可以仅包括手部按压深度检测方法运行于其上的电子设备(例如终端设备101、102、103或服务器105)。It should be understood that the numbers of terminal devices, networks and servers in Fig. 1 are only illustrative. According to the implementation needs, there can be any number of terminal devices, networks and servers. When the electronic device on which the live stream playback method runs does not need to perform data transmission with other electronic devices, the system architecture may only include the electronic devices on which the hand pressing depth detection method runs (such as terminal devices 101, 102, 103 or server 105).
本发明实施例通过视觉跟踪技术，获取最高点和最低点的位置信息，继而通过位置信息的之差，获取按压深度，检测效率、精度得到有效保障。实际实施过程中，通过手机配置的前置CCD摄像头进行拍摄按压动作，并进行数字图像处理后测量获取按压深度信息。The embodiment of the present invention obtains the position information of the highest point and the lowest point through the visual tracking technology, and then obtains the compression depth through the difference of the position information, so that the detection efficiency and accuracy are effectively guaranteed. In the actual implementation process, the front CCD camera equipped with the mobile phone is used to shoot the pressing action, and after digital image processing, the pressing depth information is measured and obtained.
影响测距精度的因素很多，但硬件因素的影响可以通过选取高分辨率的CCD摄像机、高采样频率的图像采集卡等高品质硬件，各种环境因素的限制。因为手机的款式不同，通过软件算法来提高***测距精度的方法是相对最有效的途径。通常的图像测距过程都需要在场景中增设标定物(有明显的颜色特征且长宽已知)，通过此标定物标定相机、校正图像，从而获取图像的距离精度，得到目标的测量距离。但是在心脏按压的过程中，很难设定一个长宽已知的标定物。There are many factors that affect the ranging accuracy, but the influence of hardware factors can be limited by selecting high-quality hardware such as high-resolution CCD cameras and high-sampling frequency image acquisition cards, and various environmental factors. Because the styles of mobile phones are different, the method of improving the ranging accuracy of the system through software algorithms is relatively the most effective way. The usual image ranging process needs to add a calibration object (with obvious color characteristics and known length and width) in the scene, and use this calibration object to calibrate the camera and correct the image, so as to obtain the distance accuracy of the image and obtain the measurement distance of the target. However, it is difficult to set a calibration object whose length and width are known during heart compressions.
本发明实施例采取结合传统的刻度尺测量思想，通过数字图像处理，提取出按压时的手环，通过手环移动的垂直距离，用算法辅助计算来完成保证速度和精度的测距。总体方案如图2所示。The embodiment of the present invention adopts the idea of combining the traditional scale measurement, extracts the wristband when pressed through digital image processing, and completes the distance measurement with guaranteed speed and accuracy through the vertical distance of the movement of the wristband through algorithm-assisted calculation. The overall scheme is shown in Figure 2.
通过手机前置摄像头拍摄正面的按压动作，如图3所示。将拍摄到的视频，处理成图像序列。为了保证测距的速度，需要先通过将拍摄的图像进行目标检测，并进行跟踪，在按压的最高点和最高点检测具体的位置，并完成测距。假设所述目标为手环，则从一系列图像中检测手环得到每张图像中的手环在图像坐标中的位置，并确定坐标最高点和坐标最低点的手环的位置，得到的位置之间的距离为按压深度。将每一张图像中的目标通过识别算法，识别手腕部位的手环(该手环为所述目标)，并将手环的各位置信息[x,y,w,h]，传递给跟踪模块，x为X轴坐标，y为Y轴坐标，w为宽度，h为高度。本发明的实施例采用了KCF的算法完成目标的跟踪，跟踪手腕的运动并记录目标框的坐标信息。通过记录的数据提取运动过程中的极值点，将该帧的图片输入测距模块完成最后的测距。判断是否达到5cm的按压深度，并实时显示在视频中。The front pressing action is captured by the front camera of the mobile phone, as shown in Figure 3. Process the captured video into an image sequence. In order to ensure the speed of distance measurement, it is necessary to detect and track the target through the captured image, detect the specific position at the highest point of the press and the highest point, and complete the distance measurement. Assuming that the target is a bracelet, then detect the bracelet from a series of images to obtain the position of the bracelet in each image in the image coordinates, and determine the position of the bracelet with the highest point of coordinates and the lowest point of coordinates, and the obtained position The distance between them is the compression depth. Pass the target in each image through the recognition algorithm to identify the bracelet on the wrist (the bracelet is the target), and pass the position information [x, y, w, h] of the bracelet to the tracking module , x is the X-axis coordinate, y is the Y-axis coordinate, w is the width, and h is the height. The embodiment of the present invention uses the KCF algorithm to track the target, track the movement of the wrist and record the coordinate information of the target frame. The extreme point in the motion process is extracted through the recorded data, and the picture of the frame is input into the distance measurement module to complete the final distance measurement. Judge whether the compression depth of 5cm is reached, and display it in the video in real time.
具体地，检测方法包含如下几个步骤：Specifically, the detection method includes the following steps:
S1、检测标志物(手环)的位置S1. The position of the detection marker (bracelet)
输入的视频后，首先将视频流按时间序列，将图片输入到程序中，将图片处理为固定的尺寸的图片，默认为960*540，之后的处理过程如图4所示。After inputting the video, first input the video stream into the program in time sequence, and process the picture into a fixed size picture, the default is 960*540, and the subsequent processing process is shown in Figure 4.
S11、由于手环选取的为绿色和白色相互间隔的手环结构，颜色特征明显，因此，将图片转换到HSV颜色空间，便于颜色的筛选和提取。对其的颜色的色调和亮度两方面进行直接选取阈值，通过二值化实现目标分割和检测。将HSV空间模型和其他颜色空间通过H维用圆周表示。S11. Since the bracelet is selected as a bracelet structure with green and white spaced apart from each other, the color features are obvious. Therefore, the image is converted to the HSV color space to facilitate color screening and extraction. The hue and brightness of its color are directly selected as the threshold, and the target segmentation and detection are realized through binarization. The HSV space model and other color spaces are represented by circles through the H dimension.
S12、通过hsv空间提取白色和绿色的颜色特征，并将绿色区域做膨胀和腐蚀，并和白色区域做交集运算，进一步缩小目标空间。S12. Extract white and green color features through the hsv space, expand and corrode the green area, and perform an intersection operation with the white area to further narrow the target space.
S13、设计两层的核函数的分类器结构，分别设置三个卷积核进行卷积并相加，统计核函数响应最大的点。规矩响应的值的大小判断是否存在目标，同时根据内部的绿色面积设定边框的尺寸，边框的比例按照手环的比例设置为2:5，具体过程如图5所示，图片输入到三个卷积核之后相加，输入到核函数，查看响应，统计区域响应，然后设置边框尺寸。S13. Design a classifier structure with two layers of kernel functions, respectively set three convolution kernels to perform convolution and add them together, and count the point with the largest kernel function response. The value of the rule response determines whether there is a target, and at the same time sets the size of the border according to the internal green area. The ratio of the border is set to 2:5 according to the ratio of the bracelet. The specific process is shown in Figure 5. The picture is input into three After the convolution kernel is added, input to the kernel function, view the response, count the area response, and then set the border size.
S14、为了得到较为稳定的跟踪效果，应选取圈定的目标尽量大，因此，进一步的，本发明实施例选取了白色和绿色区域的并集保证大目标，返回跟踪框[x,y,H,W]。S14. In order to obtain a relatively stable tracking effect, the delineated target should be selected as large as possible. Therefore, further, the embodiment of the present invention selects the union of white and green areas to ensure a large target, and returns the tracking frame [x, y, H, W].
S2、跟踪标志物S2, tracking markers
为了应对快速按压的视频中手环的高速移动。本发明实施例提出使用相关核运算的方法，可以保证在目标在仅仅有微弱形变，且快速移动的时候保证良好的跟踪效果，可以有效的提取出目标上下移动的轨迹。KCF算法的流程如图6所示，执行的步骤有a预计算、b训练并更新模型、c寻找目标位置；首先执行步骤a，然后针对第一帧图像执行步骤b，针对第二帧之后的图像，循环执行步骤c和b。通过相关衡量两个信号相似值的度量，如果两个信号越相似，那么其相关值就越高，在tracking的应用里，使用滤波模板，使得当它作用在跟踪目标上时，得到的响应最大，最大响应值的位置就是目标的位置。KCF的特点：实现简洁、效果好、速度快。通过循环矩阵位移产生大量样本来解决问题，并且通过离散傅里叶变换的推导，在频域计算速度极快。在缺少样本的情况下，通过简单的方法检测，连接核运算进行跟踪，保证了跟踪的泛化能力。采用KCF算法具有如下优点。In order to cope with the high-speed movement of the wristband in the fast pressing video. The embodiment of the present invention proposes a method using a correlation kernel operation, which can ensure a good tracking effect when the target is only slightly deformed and moves fast, and can effectively extract the trajectory of the target moving up and down. The flow of the KCF algorithm is shown in Figure 6. The steps to be executed include a pre-computation, b training and updating the model, and c finding the target position; first execute step a, then execute step b for the first frame of image, and for the image after the second frame image, loop through steps c and b. The measure of the similarity value of two signals is measured by correlation. If the two signals are more similar, the higher the correlation value is. In the application of tracking, the filter template is used to maximize the response when it acts on the tracking target. , the location of the maximum response value is the location of the target. The characteristics of KCF: Simple implementation, good effect and fast speed. A large number of samples are generated by cyclic matrix displacement to solve the problem, and the calculation speed in the frequency domain is extremely fast through the derivation of the discrete Fourier transform. In the case of lack of samples, it is detected by a simple method, and the core operation is connected to track, which ensures the generalization ability of the track. Using the KCF algorithm has the following advantages.
1)检测：使用循环矩阵+傅里叶变化计算响应图，原本O(n^3)的算法只需要O(n*log(n))1) Detection: use cyclic matrix + Fourier change to calculate the response graph, the original O(n^3) algorithm only needs O(n*log(n))
2)训练：利用循环矩阵性质，在频域进行训练2) Training: use the nature of the cyclic matrix to train in the frequency domain
3)核回归提速：对于核函数，也可以转化到频域进行训练和检测，大大提高速度3) Kernel regression speed up: For the kernel function, it can also be converted to the frequency domain for training and detection, greatly improving the speed
4)特殊核函数进一步加速：对于高斯核，多项式核可以进一步利用循环矩阵计算核函数的循环矩阵4) The special kernel function is further accelerated: for the Gaussian kernel, the polynomial kernel can further use the circulant matrix to calculate the circulant matrix of the kernel function
通过跟踪可以快速跟踪住实验目标。通过将人工按压的视频输入到程序中，可以稳定的显示其移动的距离。Tracking can quickly track the experimental goals. By inputting the video of manual pressing into the program, the distance it moves can be displayed stably.
S3、检测距离S3. Detection distance
在胸外按压的视频中，目标移动速度快，且距离小精度高，所以为保证测距模块，需要在参考系上进行改进。检测距离中需要考量如下因素：In the chest compression video, the target moves fast, and the distance is small and the accuracy is high. Therefore, in order to ensure the ranging module, it is necessary to improve the reference system. The following factors need to be considered in the detection distance:
A、测量位移5cm非常小，相机放置位置即使很近，信标在图像中所占像素仍很小，信标的特征提取难度较大。A. The measurement displacement of 5cm is very small. Even if the camera is placed very close, the pixels occupied by the beacon in the image are still very small, and the feature extraction of the beacon is difficult.
B、每个人的胸外按压动作各不相同，差别很大，也会对精度产生影响，需要用额外的算法弥补。B. Each person's chest compression action is different, and the difference is very large, which will also affect the accuracy, and additional algorithms need to be used to make up for it.
C、由于拍摄时的摄像头无法保证绝对的垂直和水平，按压的角度变换都会导致所测得垂直距离存在偏差C. Since the camera cannot guarantee absolute verticality and horizontality when shooting, the angle change of pressing will cause deviation in the measured vertical distance
D、相机的像素本身可能会导致精度损失，误差E可以通过如下公式获取得到。D. The pixel of the camera itself may cause a loss of precision, and the error E can be obtained by the following formula.
Figure PCTCN2021143103-appb-000001
Figure PCTCN2021143103-appb-000001
通过数学推导可知，拍摄时的实际距离的测量和像素值都会造成实验时的精度误差，增加参考距离的长度可以有效缩减实验中的误差。Through mathematical derivation, it can be seen that the measurement of the actual distance and the pixel value during shooting will cause the accuracy error during the experiment, and increasing the length of the reference distance can effectively reduce the error in the experiment.
由上面的推导，我们在实际的测距上，通过测试手环在最高点的上边沿和最低点的下边沿，保证参考的移动距离最大，减少测距所带来的的误差。同时在手环上加入特征图案logo，保证在定位上的准确性。Based on the above derivation, in the actual distance measurement, we test the wristband on the upper edge of the highest point and the lower edge of the lowest point to ensure the maximum moving distance of the reference and reduce the error caused by the distance measurement. At the same time, a characteristic pattern logo is added to the bracelet to ensure the accuracy of positioning.
本发明的实施例通过标志物跟踪方法能够利用低成本设备实现测距，降低了设备要求。克服了传统单目测距方法中需要固定参照物、精度较低、无法适应远距离测量场合的缺陷。The embodiments of the present invention can use low-cost equipment to implement distance measurement through the marker tracking method, thereby reducing equipment requirements. It overcomes the shortcomings of the traditional monocular ranging method that requires a fixed reference object, has low precision, and cannot adapt to long-distance measurement occasions.
参考图7，本发明的另一个实施例提供了一种手机按压深度检测方法，包括如下步骤：Referring to FIG. 7 , another embodiment of the present invention provides a mobile phone pressing depth detection method, including the following steps:
S21、读取目标视频，所述目标视频是由固定拍摄设备针对手部按压动作进行采集获取到的视频，所述手部上佩戴有标志物。拍摄时，被按压实验物平躺在地面，拍摄设备的位置与按压位置处于近乎同一高度，从按压动作的侧面进行拍摄录制视频。S21. Read the target video. The target video is a video captured by a fixed shooting device for the pressing action of a hand, and a marker is worn on the hand. When shooting, the subject to be pressed lies flat on the ground, the position of the shooting equipment is almost at the same height as the pressing position, and the video is shot and recorded from the side of the pressing action.
S22、对所述目标视频进行标志物检测，获取所述标志物的跟踪边框；具体地，将所述目标视频按照时间顺序生成视频帧序列；将所述视频帧图像转换到HSV颜色空间，在HSV颜色空间中，根据目标颜色，进行二值化处理，分割所述视频帧图像，获取目标颜色图像；利用N个卷积核分别对所述目标颜色图像进行卷积，并将各个卷积核的输出相加，统计核函数响应最大的点，统计响应最大的点所在区域是否大于阈值，如果大于阈值，判断存在目标，根据所述目标颜色图像的区域设定跟踪边框，其中，N为大于等于3的整数。S22. Perform marker detection on the target video, and obtain the tracking frame of the marker; specifically, generate a sequence of video frames from the target video in chronological order; convert the video frame images into HSV color space, and In the HSV color space, according to the target color, binarization processing is performed, the video frame image is segmented, and the target color image is obtained; N convolution kernels are used to convolve the target color image respectively, and each convolution kernel The output is added together, the point with the largest statistical kernel function response, whether the area where the point with the largest statistical response is located is greater than the threshold value, if greater than the threshold value, it is judged that there is a target, and the tracking frame is set according to the area of the target color image, where N is greater than An integer equal to 3.
进一步的，所述标志物上有相互间隔的第一目标颜色和第二目标颜色，所述目标颜色图像包括第一目标颜色图像和第二目标颜色图像；在进行卷积处理之前，还包括，对第二目标颜色图像进行膨胀处理和腐蚀处理，并和所述第一目标颜色图像做交集运算。Further, the first target color and the second target color are spaced apart from each other on the marker, and the target color image includes the first target color image and the second target color image; before performing convolution processing, it also includes, Dilation processing and erosion processing are performed on the second target color image, and an intersection operation is performed on the first target color image.
进一步的，所述根据所述目标颜色图像的区域设定跟踪边框，包括：根据第一目标颜色图像和第二目标颜色图像的并集区域设定所述跟踪边框。Further, setting the tracking frame according to the area of the target color image includes: setting the tracking frame according to the union area of the first target color image and the second target color image.
所述第一目标颜色为白色，所述第二目标颜色为绿色。颜色对比明显，利于检测。The first target color is white, and the second target color is green. The color contrast is obvious, which is good for detection.
S23、对所述跟踪边框进行跟踪，获取所述标志物在按压方向上的最高点和最低点；本发明实施例中可以采用KCF方法进行跟踪，也可以采用其他方法进行跟踪，跟踪过程中检测到达极值点之后，返回最高点和最低点的坐标。S23. Track the tracking frame, and obtain the highest point and the lowest point of the marker in the pressing direction; in the embodiment of the present invention, the KCF method can be used for tracking, and other methods can also be used for tracking, and detection during the tracking process After reaching the extremum point, return the coordinates of the highest point and the lowest point.
S24、根据所述最高点的坐标和最低点的坐标，获取手部按压深度。为了保证检测精度，将取更大的范围作为按压深度，具体地，所述最高点的坐标为所述标志物位于最高点时，所述标志物的上边沿的坐标，所述最低点的坐标为所述标志物位于最低点时，所述标志物的下边沿的坐标。S24. Obtain the hand pressing depth according to the coordinates of the highest point and the lowest point. In order to ensure the detection accuracy, a larger range will be taken as the pressing depth. Specifically, the coordinates of the highest point are the coordinates of the upper edge of the marker when the marker is at the highest point, and the coordinates of the lowest point is the coordinate of the lower edge of the marker when the marker is at the lowest point.
为了提示用户，所述检测方法还包括，S25、判断所述手部按压深度信息满足按压阈值，显示提示信息。例如，按压深度满足按压阈值，则显示合格，或者显示绿色。In order to prompt the user, the detection method further includes, S25, judging that the hand pressing depth information satisfies the pressing threshold, and displaying prompt information. For example, if the compression depth meets the compression threshold, it will display qualified, or display green.
本发明实施例中的手部按压深度检测方法，通过利用在最高点时最上沿的坐标和最低点时最下沿的坐标来获取按压深度，充分考量到了测量误差，保证了测量的精度。通过跟踪方法测量，降低了测距设备的性能要求，降低了方法实施的成本。The hand pressing depth detection method in the embodiment of the present invention obtains the pressing depth by using the coordinates of the uppermost edge at the highest point and the coordinates of the lowermost edge at the lowest point, fully considering the measurement error and ensuring the accuracy of the measurement. The measurement by the tracking method reduces the performance requirement of the ranging equipment and reduces the cost of method implementation.
如图8所示，依据上述的方法实施例，本发明实施例还提供了一种手部按压深度检测装置300，包括：As shown in FIG. 8, according to the above-mentioned method embodiment, the embodiment of the present invention also provides a hand pressing depth detection device 300, including:
读取模块310，用于读取目标视频，所述目标视频是由固定拍摄设备针对手部按压动作进行采集获取到的视频，所述手部上佩戴有标志物；The reading module 310 is used to read the target video, the target video is a video captured by the fixed shooting device for the pressing action of the hand, and the hand is worn with a marker;
检测模块320，用于对所述目标视频进行标志物检测，获取所述标志物的跟踪边框；A detection module 320, configured to perform marker detection on the target video, and obtain a tracking frame of the marker;
跟踪模块330，对所述跟踪边框进行跟踪，获取所述标志物在按压方向上的最高点和最低点；The tracking module 330 is configured to track the tracking frame, and obtain the highest point and the lowest point of the marker in the pressing direction;
测距模块340，用于根据所述最高点的坐标和最低点的坐标，获取手部按压深度。The ranging module 340 is configured to obtain the hand pressing depth according to the coordinates of the highest point and the lowest point.
上述各个模块的具体执行步骤在直播流播放方法中对应的步骤中已进行详细叙述，在此不做过多赘述。The specific execution steps of the above modules have been described in detail in the corresponding steps in the live stream playing method, and will not be repeated here.
下面参考图9，其示出了适于用来实现本申请实施例的控制设备的计算机***800的结构示意图。图9示出的控制设备仅仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。Referring now to FIG. 9 , it shows a schematic structural diagram of a computer system 800 suitable for implementing the control device of the embodiment of the present application. The control device shown in FIG. 9 is only an example, and should not limit the functions and scope of use of this embodiment of the present application.
如图9所示，计算机***800包括中央处理单元(CPU)801，其可以根据存储在只读存储器(ROM)802中的程序或者从存储部分808加载到随机访问存储器(RAM)803中的程序而执行各种适当的动作和处理。在RAM 803中，还存储有***800操作所需的各种程序和数据。CPU 801、ROM 802以及RAM 803通过总线804彼此相连。输入/输出(I/O)接口805也连接至总线804。As shown in FIG. 9 , a computer system 800 includes a central processing unit (CPU) 801 that can be programmed according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage section 808 into a random-access memory (RAM) 803 Instead, various appropriate actions and processes are performed. In the RAM 803, various programs and data required for the operation of the system 800 are also stored. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input/output (I/O) interface 805 is also connected to the bus 804 .
以下部件连接至I/O接口805：包括键盘、鼠标等的输入部分806；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分807；包括硬盘等的存储部分808；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分809。通信部分809经由诸如因特网的网络执行通信处理。驱动器810也根据需要连接至I/O接口805。可拆卸介质811，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器810上，以便于从其上读出的计算机程序根据需要被安装入存储部分808。The following components are connected to the I/O interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 808 including a hard disk, etc. and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I/O interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 810 as necessary so that a computer program read therefrom is installed into the storage section 808 as necessary.
特别地，根据本公开的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本公开的实施例包括一种计算机程序产品，其包括承载在计算机可读介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中，该计算机程序可以通过通信部分809从网络上被下载和安装，和/或从可拆卸介质811被安装。在该计算机程序被中央处理单元(CPU)801执行时，执行本申请的方法中限定的上述功能。In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, where the computer program includes program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via communication portion 809 and/or installed from removable media 811 . When the computer program is executed by the central processing unit (CPU) 801, the above-mentioned functions defined in the method of the present application are performed.
需要说明的是，本申请所述的计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质或者是上述两者的任意组合。计算机可读存储介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的***、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子可以包括但不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本申请中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行***、装置或者器件使用或者与其结合使用。而在本申请中，计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行***、装置或者器件使用或者与其结合使用的程序。计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于：无线、电线、光缆、RF等等，或者上述的任意合适的组合。It should be noted that the computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable Programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, in which computer-readable program codes are carried. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. . Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
可以以一种或多种程序设计语言或其组合来编写用于执行本申请的操作的计算机程序代码，所述程序设计语言包括面向目标的程序设计语言—诸如Python、Java、Smalltalk、C++，还包括常规的过程式程序设计语言—诸如“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中，远程计算机可以通过任意种类的网络——包括局域网(LAN)或广域网(WAN)—连接到用户计算机，或者，可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。Computer program code for carrying out the operations of this application can be written in one or more programming languages, or combinations thereof, including object-oriented programming languages—such as Python, Java, Smalltalk, C++, and Includes conventional procedural programming languages - such as the "C" language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as through an Internet service provider). Internet connection).
附图中的流程图和框图，图示了按照本申请各种实施例的***、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个 模块、程序段、或代码的一部分，该模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的***来实现，或者可以用专用硬件与计算机指令的组合来实现。The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or portion of code that contains one or more logical functions for implementing specified executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified functions or operations , or may be implemented by a combination of dedicated hardware and computer instructions.
描述于本申请实施例中所涉及到的单元可以通过软件的方式实现，也可以通过硬件的方式来实现。所描述的单元也可以设置在处理器中，例如，可以描述为：一种处理器包括获取单元、分割单元、确定单元和选择单元。其中，这些单元的名称在某种情况下并不构成对该单元本身的限定，例如，获取单元还可以被描述为“获取待处理绘本图像的单元”。The units involved in the embodiments described in the present application may be implemented by means of software or by means of hardware. The described units may also be set in a processor, for example, it may be described as: a processor includes an acquiring unit, a dividing unit, a determining unit and a selecting unit. Wherein, the names of these units do not constitute a limitation on the unit itself under certain circumstances, for example, the acquisition unit may also be described as "a unit for acquiring picture book images to be processed".
作为另一方面，本申请还提供了一种计算机可读介质，该计算机可读介质可以是上述实施例中描述的电子设备中所包含的；也可以是单独存在，而未装配入该电子设备中。上述计算机可读介质承载有一个或者多个程序，当上述一个或者多个程序被该电子设备执行时，使得该电子设备：读取目标视频，所述目标视频是由固定拍摄设备针对手部按压动作进行采集获取到的视频，所述手部上佩戴有标志物；对所述目标视频进行标志物检测，获取所述标志物的跟踪边框；对所述跟踪边框进行跟踪，获取所述标志物在按压方向上的最高点和最低点；根据所述最高点的坐标和最低点的坐标，获取手部按压深度。As another aspect, the present application also provides a computer-readable medium. The computer-readable medium may be included in the electronic device described in the above embodiments; it may also exist independently without being assembled into the electronic device. middle. The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device: reads the target video, and the target video is pressed by the fixed shooting device against the hand Actions are collected to obtain the video, and the hands are worn with markers; marker detection is performed on the target video, and the tracking frame of the marker is acquired; the tracking frame is tracked, and the marker is acquired The highest point and the lowest point in the pressing direction; according to the coordinates of the highest point and the lowest point, the pressing depth of the hand is obtained.
以上描述仅为本申请的较佳实施例以及对所运用技术原理的说明。本领域技术人员应当理解，本申请中所涉及的发明范围，并不限于上述技术特征的特定组合而成的技术方案，同时也应涵盖在不脱离上述发明构思的情况下，由上述技术特征或其等同特征进行任意组合而形成的其它技术方案。例如上述特征与本申请中公开的(但不限于)具有类似功能的技术特征进行互相替换而形成的技术方案。The above description is only a preferred embodiment of the present application and an illustration of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solution formed by the specific combination of the above-mentioned technical features, and should also cover the technical solution formed by the above-mentioned technical features or Other technical solutions formed by any combination of equivalent features. For example, a technical solution formed by replacing the above-mentioned features with technical features with similar functions disclosed in (but not limited to) this application.

Claims (11)

  1. 一种手部按压深度检测方法，其特征在于，包括如下步骤：A hand pressing depth detection method is characterized in that, comprising the steps of:
    读取目标视频，所述目标视频是由固定拍摄设备针对手部按压动作进行采集获取到的视频，所述手部上佩戴有标志物；Reading the target video, the target video is a video captured by a fixed shooting device for the pressing action of the hand, and the hand is worn with a marker;
    对所述目标视频进行标志物检测，获取所述标志物的跟踪边框；Perform marker detection on the target video, and obtain a tracking frame of the marker;
    对所述跟踪边框进行跟踪，获取所述标志物在按压方向上的最高点和最低点；Tracking the tracking frame to obtain the highest point and the lowest point of the marker in the pressing direction;
    根据所述最高点的坐标和最低点的坐标，获取手部按压深度。According to the coordinates of the highest point and the coordinates of the lowest point, the pressing depth of the hand is obtained.
  2. 根据权利要求1所述的手部按压深度检测方法，其特征在于，所述最高点的坐标为所述标志物位于最高点时，所述标志物的上边沿的坐标；所述最低点的坐标为所述标志物位于最低点时，所述标志物的下边沿的坐标。The hand pressing depth detection method according to claim 1, wherein the coordinates of the highest point are the coordinates of the upper edge of the marker when the marker is at the highest point; the coordinates of the lowest point is the coordinate of the lower edge of the marker when the marker is at the lowest point.
  3. 根据权利要求1或2所述的手部按压深度检测方法，其特征在于，所述对所述目标视频进行标志物检测的步骤包括：The hand pressing depth detection method according to claim 1 or 2, wherein the step of performing marker detection on the target video comprises:
    将所述目标视频按照时间顺序生成视频帧序列；Generating a sequence of video frames from the target video in chronological order;
    将所述视频帧图像转换到HSV颜色空间，在HSV颜色空间中，根据目标颜色，进行二值化处理，分割所述视频帧图像，获取目标颜色图像；Converting the video frame image to the HSV color space, in the HSV color space, according to the target color, perform binarization processing, segment the video frame image, and obtain the target color image;
    利用N个卷积核分别对所述目标颜色图像进行卷积，并将各个卷积核的输出相加，统计核函数响应最大的点，统计响应最大的点所在区域是否大于阈值，如果大于阈值，判断存在目标，根据所述目标颜色图像的区域设定跟踪边框，其中，N为大于等于3的整数。Use N convolution kernels to convolve the target color image respectively, and add the outputs of each convolution kernel, and count the point with the largest kernel function response, and whether the area where the point with the largest statistical response is located is greater than the threshold, if it is greater than the threshold , determine that there is a target, and set a tracking frame according to the area of the target color image, where N is an integer greater than or equal to 3.
  4. 根据权利要求3所述的手部按压深度检测方法，其特征在于，所述标志物上有相互间隔的第一目标颜色和第二目标颜色，所述目标颜色图像包括第一目标颜色图像和第二目标颜色图像；在进行卷积处理之前，还包括，对第二目标颜色图像进行膨胀处理和腐蚀处理，并和所述第一目标颜色图像做交集运算。The method for detecting the depth of hand pressing according to claim 3, wherein the first target color and the second target color are spaced apart from each other on the marker, and the target color image includes the first target color image and the second target color image. The second target color image: before performing convolution processing, it also includes performing expansion processing and erosion processing on the second target color image, and performing an intersection operation with the first target color image.
  5. 根据权利要求4所述的手部按压深度检测方法，其特征在于，所述根据所述目标颜色图像的区域设定跟踪边框，包括：根据第一目标颜色图像和第二目标颜色图像的并集区域设定所述跟踪边框。The method for detecting the depth of hand pressing according to claim 4, wherein setting the tracking frame according to the region of the target color image comprises: according to the union of the first target color image and the second target color image Region sets the tracking bounding box.
  6. 根据权利要求4所述的手部按压深度检测方法，其特征在于，所述第一目标颜色为白色，所述第二目标颜色为绿色。The method for detecting the depth of hand pressing according to claim 4, wherein the first target color is white, and the second target color is green.
  7. 根据权利1或2所述的手部按压深度检测方法，其特征在于，对所述标志物进行跟踪的步骤包括：采用KCF算法对所述标志物进行跟踪。The method for detecting the depth of hand pressing according to claim 1 or 2, characterized in that the step of tracking the markers includes: tracking the markers using the KCF algorithm.
  8. 根据权利要求1或2所述的手部按压深度检测方法，其特征在于，所述检测方法还包括，判断所述手部按压深度信息满足按压阈值，显示提示信息。The method for detecting hand pressing depth according to claim 1 or 2, further comprising: judging that the hand pressing depth information satisfies a pressing threshold, and displaying prompt information.
  9. 一种手部按压深度检测装置，其特征在于，包括：A hand pressing depth detection device is characterized in that it comprises:
    读取模块，用于读取目标视频，所述目标视频是由固定拍摄设备针对手部按压动作进行采集获取到的视频，所述手部上佩戴有标志物；The reading module is used to read the target video, the target video is a video captured by the fixed shooting device for the pressing action of the hand, and the hand is worn with a marker;
    检测模块，用于对所述目标视频进行标志物检测，获取所述标志物的跟踪边框；A detection module, configured to perform marker detection on the target video, and obtain a tracking frame of the marker;
    跟踪模块，对所述跟踪边框进行跟踪，获取所述标志物在按压方向上的最高点和最低点；A tracking module, which tracks the tracking frame and obtains the highest point and the lowest point of the marker in the pressing direction;
    测距模块，用于根据所述最高点的坐标和最低点的坐标，获取手部按压深度。The ranging module is configured to obtain the hand pressing depth according to the coordinates of the highest point and the lowest point.
  10. 一种电子设备，包括：An electronic device comprising:
    一个或多个处理器；one or more processors;
    存储装置，其上存储有一个或多个程序，a storage device on which one or more programs are stored,
    当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现如权利要求1-8中任一所述的方法。When the one or more programs are executed by the one or more processors, the one or more processors are made to implement the method according to any one of claims 1-8.
  11. 一种计算机可读介质，其上存储有计算机程序，其中，所述程序被处理器执行时实现如权利要求1-8中任一所述的方法。A computer-readable medium, on which a computer program is stored, wherein when the program is executed by a processor, the method according to any one of claims 1-8 is implemented.
PCT/CN2021/143103 2021-12-30 2021-12-30 Hand pressing depth measurement method and apparatus WO2023123213A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
PCT/CN2021/143103 WO2023123213A1 (en) 2021-12-30 2021-12-30 Hand pressing depth measurement method and apparatus
CN202180005746.XA CN114556447A (en) 2021-12-30 2021-12-30 Hand pressing depth detection method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2021/143103 WO2023123213A1 (en) 2021-12-30 2021-12-30 Hand pressing depth measurement method and apparatus

Publications (1)

Publication Number Publication Date
WO2023123213A1 true WO2023123213A1 (en) 2023-07-06

Family

ID=81668986

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/143103 WO2023123213A1 (en) 2021-12-30 2021-12-30 Hand pressing depth measurement method and apparatus

Country Status (2)

Country Link
CN (1) CN114556447A (en)
WO (1) WO2023123213A1 (en)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011011633A2 (en) * 2009-07-22 2011-01-27 Atreo Medical, Inc. Optical techniques for the measurement of chest compression depth and other parameters during cpr
JP2013153847A (en) * 2012-01-27 2013-08-15 Kissei Comtec Co Ltd Cardiac massage support device and cardiac massage supporting computer program
CN109313934A (en) * 2016-05-06 2019-02-05 皇家飞利浦有限公司 For determining the CPR ancillary equipment and method of patient chest according to pressing depth
CN113317975A (en) * 2021-06-25 2021-08-31 河南金芯数联电子科技有限公司 Cardio-pulmonary resuscitation pressing depth feedback system based on machine vision
CN214752528U (en) * 2021-03-16 2021-11-16 敖然 Portable cardiopulmonary resuscitation guides device

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102164573B (en) * 2008-07-23 2015-12-02 菲希欧控制加拿大销售有限公司 For measuring the CPR auxiliary device of pressing parameter during cardio-pulmonary resuscitation
BR112016002744A2 (en) * 2013-08-13 2017-08-01 Koninklijke Philips Nv system for providing feedback, automated resuscitation device, computer program stored in a medium or distributed via a wired or wireless telecommunication system, and method for providing feedback
US10561575B2 (en) * 2016-03-31 2020-02-18 Zoll Medical Corporation Monitoring CPR by a wearable medical device
CN112292688A (en) * 2020-06-02 2021-01-29 焦旭 Motion detection method and apparatus, electronic device, and computer-readable storage medium
CN112712051A (en) * 2021-01-12 2021-04-27 腾讯科技（深圳）有限公司 Object tracking method and device, computer equipment and storage medium

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011011633A2 (en) * 2009-07-22 2011-01-27 Atreo Medical, Inc. Optical techniques for the measurement of chest compression depth and other parameters during cpr
JP2013153847A (en) * 2012-01-27 2013-08-15 Kissei Comtec Co Ltd Cardiac massage support device and cardiac massage supporting computer program
CN109313934A (en) * 2016-05-06 2019-02-05 皇家飞利浦有限公司 For determining the CPR ancillary equipment and method of patient chest according to pressing depth
CN214752528U (en) * 2021-03-16 2021-11-16 敖然 Portable cardiopulmonary resuscitation guides device
CN113317975A (en) * 2021-06-25 2021-08-31 河南金芯数联电子科技有限公司 Cardio-pulmonary resuscitation pressing depth feedback system based on machine vision

Also Published As

Publication number Publication date
CN114556447A (en) 2022-05-27

Similar Documents

Publication Publication Date Title
WO2021083242A1 (en) Map constructing method, positioning method and system, wireless communication terminal, and computer-readable medium
WO2022170742A1 (en) Target detection method and apparatus, electronic device and storage medium
US10796438B2 (en) Method and apparatus for tracking target profile in video
WO2018176938A1 (en) Method and device for extracting center of infrared light spot, and electronic device
CN109858333B (en) Image processing method, image processing device, electronic equipment and computer readable medium
WO2020056903A1 (en) Information generating method and device
WO2019149186A1 (en) Method and apparatus for generating information
CN107220652B (en) Method and device for processing pictures
CN113971751A (en) Training feature extraction model, and method and device for detecting similar images
US20220358675A1 (en) Method for training model, method for processing video, device and storage medium
TW202209254A (en) Image segmentation method, electronic equipment and computer-readable storage medium thereof
KR20120044484A (en) Apparatus and method for tracking object in image processing system
TWI778552B (en) Motion detection method and device, electronic device, and computer-readable recording medium with stored program
WO2023169281A1 (en) Image registration method and apparatus, storage medium, and electronic device
CN110110666A (en) Object detection method and device
CN110956131B (en) Single-target tracking method, device and system
JP7176616B2 (en) Image processing system, image processing apparatus, image processing method, and image processing program
WO2022095318A1 (en) Character detection method and apparatus, electronic device, storage medium, and program
CN117197405A (en) Augmented reality method, system and storage medium for three-dimensional object
WO2023123213A1 (en) Hand pressing depth measurement method and apparatus
US11647294B2 (en) Panoramic video data process
CN111310595A (en) Method and apparatus for generating information
CN108446737B (en) Method and device for identifying objects
CN113313735B (en) Panoramic video data processing method and device
CN113315914B (en) Panoramic video data processing method and device

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21969575

Country of ref document: EP

Kind code of ref document: A1