Automatic detection technology of sports athletes based on image recognition technology

Guangjing, Li; Zhang, Cuiping

doi:10.1186/s13640-019-0415-x

Cited by 24 publications

(9 citation statements)

References 15 publications

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“…When using the above steps to track the target, the Cam Shift algorithm calculates the centroid and area of the window within the range of the search window and resets the position and size of the next search window according to the calculation results [19].…”

Section: Applying the Cam Shift Algorithm To Track Targetsmentioning

confidence: 99%

Improved Cam Shift Algorithm for Detecting Athletes' Action Targets in Sports Videos

Yuan

2022

Mathematical Problems in Engineering

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The detection and tracking of athletes in sports videos is of great importance, as it helps to automate the analysis of sports videos, thus providing advanced tools and instruments for sports training. The Cam Shift algorithm uses the colour information of objects to achieve tracking of moving targets, so it is very important to choose a suitable colour space when obtaining the colour information of objects. To this end, this paper improves the Cam Shift algorithm by converting the visual system mechanism to perceive the colour characteristics of the image processing, i.e., converting the video image from the RGB colour space to the HSV colour space, using the H (hue) component to model the target object. Experiments show that the improved athlete detection and tracking algorithm is more robust in practical applications. The improved tracking algorithm also has better real-time performance, with a processing speed of 20 fps during the experiments.

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Section: Applying the Cam Shift Algorithm To Track Targetsmentioning

confidence: 99%

Improved Cam Shift Algorithm for Detecting Athletes' Action Targets in Sports Videos

Yuan

2022

Mathematical Problems in Engineering

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“…The purpose is to extract factors through factor analysis to see whether the structure between these factors is consistent with the conceived structure. If they are completely consistent, the structural validity is high [27], [28]. First, a factor suitability test was performed, and the Bartlett spherical test was performed on the data of the empathy ability questionnaire of the youth.…”

Section: B Evaluation Of Empathy Ability Based On Data Envelopmentioning

confidence: 99%

Research on Screening of Empathy Information Based on Image Recognition and Data Mining

et al. 2020

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The Internet not only provides help for people to understand the world and facilitate life, but also provides a convenient way for widespread dissemination of bad information. It follows that young people are often harassed by pornographic, violent and other bad images, which affects the development of young people's empathy. In this study, from the perspective of the combination of bad image screening and youth empathy ability, the effect of bad image on youth empathy ability is studied. In this article, a new empathy analysis model is constructed based on traditional empathy theory, combined with image recognition and data mining technology. First, the theoretical principles of bad image recognition technology and their application in the evaluation of empathy ability are expounded. Then, based on image recognition and fusion particle swarm optimization algorithm, the classification of bad images was studied. Finally, on the basis of image classification, a data envelopment model is used to grade the young people's empathy ability. The actual case analysis and performance test results illustrate the superiority of the implemented image classification and empathy evaluation method based on image recognition and data mining. This research has certain theoretical significance for the research of enriching empathy ability and interpersonal relationship. At the same time, it has certain practical significance for improving the youth's interpersonal trust, realizing the harmonious interpersonal relationship and the healthy development of body and mind.

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“…With its parallel acceleration processing characteristics [4], FPGA can perform hardware acceleration, which can greatly improve the image processing speed. Among them, due to the exponential growth of hardware facilities such as cameras [5], surveillance equipment, and mobile phones [6], the research demand for automatic video analysis of moving object detection and tracking has shown explosive growth [7].…”

Section: Introductionmentioning

confidence: 99%

FPGA-based single-target motion detection design

Yin,

Sun

2023

Third International Conference on Signal Image Processing and Communication (ICSIPC 2023)

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For research at home and abroad, and to ensure the accuracy and real-time of the acquired images, to achieve the function of moving target detection, a digital image processing application based on FPGA - moving object detection is proposed, and the image acquisition and image processing two parts are studied, the image acquisition is OMINIVISION OV5640 image sensor, which comes with an embedded microprocessor to support image scaling and translation. By the programmable device FPGA to receive and send data to the FPGA external large-capacity SDRAM memory for storage, image processing is selected Intel Cyclone IV series FPGA chip, for the image acquisition process of a variety of random noise, through the verilog HDL hardware description language written RTL register transmission level code, to achieve image acquisition and storage, average filtering, expansion algorithm, corrosion algorithm, morphological operation closed calculation design The processed image is used for moving target detection and VGA display display. The system is mainly composed of camera acquisition module, SDRAM controller module, display driver module, image processing module, through design simulation, the results show that the system realizes real-time acquisition and processing of digital images, reaching 640*480 resolution display of 30 frames per second.

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Automatic detection technology of sports athletes based on image recognition technology

Cited by 24 publications

References 15 publications

Improved Cam Shift Algorithm for Detecting Athletes' Action Targets in Sports Videos

Improved Cam Shift Algorithm for Detecting Athletes' Action Targets in Sports Videos

Research on Screening of Empathy Information Based on Image Recognition and Data Mining

FPGA-based single-target motion detection design

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