Improved Biological Image Tracking Algorithm of Athlete’s Cervical Spine Health

Dai, Chunmin; Yang, Long

doi:10.1590/1517-8692202127032021_0129

Cited by 4 publications

(6 citation statements)

References 8 publications

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“…During the operation, the data information goes through the operation of each convolutional layer. The calculation performed by the neural network is actually the dot product of the input value vector and the weight matrix of each layer to obtain the final output result [ 17 ]. Backpropagation stage It comes out to define the cost function loss:

where x is the number of samples in the sample set, and W is the number of layers of the convolutional neural network.…”

Section: Continuous Deep Learning System Research Methods For Tennis ...mentioning

confidence: 99%

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A Continuous Deep Learning System Study of Tennis Player Health Information and Professional Input

Gong

2022

Computational Intelligence and Neuroscience

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The health status of elite tennis players and the results of tennis matches are positively proportional under normal circumstances. The physical and psychological functions of tennis players directly affect the athletic ability of tennis players. With the improvement of people’s living standards, people’s attention to tennis has also increased. Tennis has received increasing attention in China, and the training of tennis players has become increasingly necessary. However, China is still using the traditional means of obtaining athletes’ health information to evaluate athletes’ health information. This has led to imperfect research into tennis players’ health information and professional input systems. This makes the understanding of the health information of athletes incomplete and profound, and it affects the athletic ability of athletes. In this paper, deep learning and a two-factor model are added to tennis players’ health information and professional input, and the feasibility of a deep learning system to comprehensively improve health information input is explored. The experimental results show that the application of the convolutional neural network method in the system improves the response speed to the physical fitness state of tennis players by 5%. This adds technical support for timely understanding of tennis players’ physical health information and prevents players from making mistakes on the court due to physical reasons.

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where x is the number of samples in the sample set, and W is the number of layers of the convolutional neural network.…”

Section: Continuous Deep Learning System Research Methods For Tennis ...mentioning

confidence: 99%

Section: Continuous Deep Learning System Research Methods For Tennis ...mentioning

confidence: 99%

A Continuous Deep Learning System Study of Tennis Player Health Information and Professional Input

Gong

2022

Computational Intelligence and Neuroscience

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“…Dai and Lu investigated an improved bioimage tracking algorithm under color feedback for cervical spine health of athletes. The aim is to propose a new algorithm to improve the accuracy of detection and tracking [7]. Jiang addresses the shortcomings and deficiencies of conventional object inspection as well as target detection algorithms in different scenarios and proposes a target detection and tracking algorithm according to the current status and technology level of domestic and foreign object inspection and tracking research.…”

Section: Related Workmentioning

confidence: 99%

Health Detection System for Sports Dancers during Training Based on an Image Processing Technology

Zhang

2022

Applied Bionics and Biomechanics

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Dance sport is a competition of athletes for qualities such as speed, strength, endurance, flexibility, and coordination, requiring a high level of overall physical fitness. As China’s sports fever continues to heat up, especially among students, the active nature of young people can lead to overenthusiasm for sports, dance, and other sports, which can lead to various physical discomforts during sports. Especially in the current sports habits of students, there is a great hidden danger of sports injuries. It is mainly due to excessive exercise, irregular exercise methods, and incomplete sports protective equipment. On this basis, this study proposes a model to further assess the health status of individuals and groups from the rate of energy consumption during exercise by building a real-time motion detection system. The development of sports health assessment systems, including the application of imaging techniques, is also analyzed. The experimental results in this article show that when the error threshold is set to 10%, the accuracy of the model is 85%, and the obtained results are ideal.

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“…Dai and Lu studied an improved bioimage tracking algorithm for athletes' cervical spine health under color feedback. Their aim was to propose a new algorithm to improve the detection and tracking accuracy [10]. To assist football training in colleges and universities, Zhu proposed an edge computing-based football robot path planning algorithm and an improved PSO (particle swarm optimization) algorithm [11].…”

Section: Related Workmentioning

confidence: 99%

“…In formula (10) and formula (11), Iðx, yÞ represents the gray value at ðx, yÞ; then, the modulus value and direction of the directional gradient at the ðx, yÞ point can be expressed as As shown in Figure 2, this design can better optimize the detector or tracker to a certain extent for the tracking effect and can basically achieve the effect of real-time tracking. The speed can be adjusted according to the scale of Re-ID.…”

Section: Hog Feature Extractionmentioning

confidence: 99%

Intelligent Optimization Algorithm of 3D Tracking Technology in Football Player Moving Image Analysis

Sun

Zhao

et al. 2022

Wireless Communications and Mobile Computing

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Computer vision technology began to affect the development of football. There is increasingly high-tech in football broadcast technology, and many application tools have emerged in the field of football broadcast video analysis. The purpose of this paper is to study the improvement of target tracking algorithm for football broadcast video and to study the intelligent optimization algorithm of 3D tracking technology in football player moving image analysis. This paper proposes to select four models of YOLOv5 to perform target detection experiments in football broadcast videos and analyzes the principle of the Deep SORT multitarget tracking algorithm. At the same time, it is based on the 3D tracking and 3D pose estimation of players based on cross-view correlation matching, and to measure the comprehensive performance of the tracker in the football scene, experiments are carried out on the accuracy and speed of the tracker under the football datasets of four different scenes. The experimental results in this paper show that the MOTA values corresponding to the 3D tracking results and 2D projection results obtained in the campus dataset are only 50 and 56.2. This is much lower than the tracking performance when based on other similarity matrices. The MOTA value of the obtained tracking result (92.6) is very close and significantly outperforms other methods. CCOT performs better on datasets 28, 29, 31, and 32, ECO stands out on dataset 38, and Siamese also performs well on datasets 22 and 36.

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Improved Biological Image Tracking Algorithm of Athlete’s Cervical Spine Health

Cited by 4 publications

References 8 publications

A Continuous Deep Learning System Study of Tennis Player Health Information and Professional Input

A Continuous Deep Learning System Study of Tennis Player Health Information and Professional Input

Health Detection System for Sports Dancers during Training Based on an Image Processing Technology

Intelligent Optimization Algorithm of 3D Tracking Technology in Football Player Moving Image Analysis

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