Sports Image Research Articles

Athlete body fat rate monitoring and motion image simulation based on SDN data center network and sensors

With the development of artificial intelligence technology, new software is also emerging in an endless stream. On the basis of sensors, the new software realizes the separation of network control layer and data layer, thereby improving network throughput and link utilization. With the gradual maturity of deep reinforcement learning technology, the redefined network architecture can be managed and controlled through software, making the network evolve toward a more intelligent direction. By providing data support for the intelligent control of the network, the network controller can obtain the data transmission status in real time, so that more ideas can become reality. Now, on the basis of motion sensors, through data fusion technology, athletes' physical conditions can be planned more effectively, so as to achieve scientific management and reasonable planning, obtain more accurate body fat rates, and customize corresponding data flow routing strategies., To achieve the combination of technology and technology. This paper proposes a scheduling strategy based on machine learning, combining the reinforcement learning algorithm in machine learning and deep reinforcement learning algorithm, setting the key factors of reinforcement learning, and applying it to real-time sports images of athletes, combining the sports characteristics of athletes, Set the action and reward value. Then use the algorithm to allocate a reasonable path for data transmission according to the real-time status to reduce network delay. This article will use sensor technology and data center network to provide a new method for athletes' real-time motion images and body fat percentage.

Incidental Findings in Sports Imaging

This narrative review presents a series of cases of less common incidental findings discovered on magnetic resonance imaging of elite athletes, who have presented for investigation of either muscle or joint sports-related injuries or for presigning imaging. The presented incidental findings include anatomical variants of osseous structures and muscles; incidental bone lesions; examples of systemic disease, and nonorthopedic findings found within the imaging field of view. This review will emphasize to the reader about the importance of interrogating the imaging in its entirety and avoiding the common pitfall of “satisfaction of search” within diagnostic radiology.

A Vision Comprehension-Driven Intelligent Recognition Approach for Actions of Tennis Players Based on Improved Convolution Neural Networks

In this paper, we focus on two tasks: semantic segmentation and target detection in the visual semantic understanding of tennis sports images and we optimize the network structure to achieve a more complete location contour information mining of the target. In detail, we focus on a weakly supervised image semantic segmentation method based on null convolution pixel relations. To address the problem of incomplete pixel-level pseudo-labeling, we introduce a cavity convolution unit with multiple cavity rates and a self-attentive mechanism in the classification model to adaptively enhance the target regions and suppress other irrelevant regions while expanding the perceptual field to generate high-quality pixel-level pseudo-labeling and then train the semantic segmentation model. The final experimental results show that the hierarchical fusion algorithm proposed in this paper significantly outperforms other algorithms, and the overall classification accuracy of the tandem cavity neural network algorithm reaches 81% with good overall classification results. The recognition accuracy of static movements is higher than that of dynamic movements.

Retracted: Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm.

[This retracts the article DOI: 10.1155/2022/3814252.].

Research on human behavior recognition method of sports images based on machine learning

Research on human behavior recognition method of sports images based on machine learning

Application of Depth Learning Algorithm in Automatic Processing and Analysis of Sports Images

Application of Depth Learning Algorithm in Automatic Processing and Analysis of Sports Images

Multi-target trajectory tracking in multi-frame video images of basketball sports based on deep learning

INTRODUCTION: There is occlusion interference in the multi-target visual tracking process of basketball video images, which leads to poor accuracy of multi-target trajectory tracking. This paper studies the multi-target trajectory tracking method in multi-frame video images of basketball sports based on deep learning. OBJECTIVES: Aiming at the problem of target occlusion in the tracking process and the problem of trajectory tracking anomaly caused by target occlusion, a modified algorithm is proposed. METHODS: The method is divided into two parts: detection and tracking. In the detection part, the YOLOv3 algorithm in deep learning technology is used to detect each target in the video, and the original YOLOv3 backbone network Darknet-53 is replaced by the lightweight backbone network MobileNetV2 to extract the target features. RESULTS: Based on the target detection results, the Kalman filter is used to predict the next position and bounding box size of the target to obtain the target trajectory prediction results according to the current target position, then a hierarchical data association algorithm is designed, and multi-target tracking of the same category is completed based on the target appearance feature similarity and feature similarity. CONCLUSION: The experimental results show that the method can accurately detect the targets in multi-frame video images in basketball sports and obtain high-precision target trajectory tracking results.

New trend to hire NIL general managers brings benefits, risks to athletics departments

After only a little more than a year into the name, image, and likeness era of college sports, student‐athletes have gone from not being permitted to receive any compensation for their NIL to giant brands, like Meta and adidas, writing checks and providing NIL education services to student‐athletes at colleges across the country. Furthermore, according to early estimates, spending in the first year of the NIL era approached $1 billion and may far surpass that figure in the coming years. The industry, which hasn't been around that long, is rapidly growing and more companies and interested parties are starting to engage in this space, despite a lack of guardrails.

Sports Image, Attitudes, and Positive Psychological Capital of MZ-Generation Viewers in the 2020 Tokyo Olympic Games Depending on Medal-Winning Status

Each generation of modern society has lived in varying environments, and different reactions occur while viewing sports. This study compared and analyzed sports, sports attitudes, and positive psychological capital of two groups according to the presence or absence of medals in the event that most impressed them after watching the 2020 Tokyo Olympics. In total, 328 survey responses were collected, and the differences between the groups were statistically verified using multivariate analysis of variance. The results showed that Group 1, which was impressed by a medal-winning event, had a relatively higher average value of self-efficacy than Group 2, which was impressed by an event in which a medal was not won. In contrast, Group 2 had a higher positive image and more resilience than did Group 1. In addition, different psychological attitudes were found in the results of factors (behavioral image, evaluative image, cognitive attitude, affective attitude, behavioral attitude, and optimism) that were not statistically significant in the differences between the groups compared to those of the previous generation. The results of this study can be used as meaningful data in sports viewing-related studies.

New trend to hire NIL general managers brings benefits, risks

After only a little more than a year into the name, image, and likeness era of college sports, student-athletes have gone from not being permitted to receive any compensation for their NIL to giant brands, like Meta and adidas, writing checks and providing NIL education services to student-athletes at colleges across the country.

Retraction Note: Analysis of sports image detection technology based on machine learning

Retraction Note: Analysis of sports image detection technology based on machine learning

Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images

In order to improve the detection and identification ability of sports injury ultrasound medicine, a segmentation method of sports injury ultrasound medical image based on local features is proposed, and the research on the sports injury ultrasound medical detection and identification ability is carried out. Methods of the sports injury ultrasound medical image segmentation model are established; the sports injury ultrasound medical image information is enhanced by using the sports skeletal muscle block matching technology; the image features are extracted; and the characteristics of sports injury ultrasound medical images are analyzed by CT bright spot feature transmission. In detail, combined with the deep convolutional neural network training method, the extracted sports injury points are automatically detected for sports injury ultrasound medical images, and the sports injury ultrasound medical image segmentation is realized. The simulation results show that this method has high accuracy for sports injury ultrasound medical image segmentation, the error value can be controlled below 0.103, and finally, the effect of zero error is achieved. It is confirmed that the method proposed in this paper has high resolution and accuracy for sports injury point detection and has strong practical application ability.

Криминологические проблемы российского спорта

The modern Russian Criminal Code provides for criminal liability for unlawfully influencing the result of a sports competition (fixed match), as well as for inducing an athlete to use or for using substances and (or) methods and means prohibited in sports against an athlete. In December 2021, the State Duma passed the first reading of the draft law on combating fixed matches. Russia is a party to international acts aimed at combating manipulation of the results of sports competitions and doping. Serious work is underway in the country to restore the sports image after the doping scandals of 2014. At the same time, official judicial statistics do not allow us to fully assess the real size of crime committed in the field of sports. There are practically no criminal cases. A significant factor that makes it difficult to understand the true state of affairs in the field of sports is its closeness and autonomy. Although articles about fixed matches and doping are systematically published in the media. It was these problems that determined the need for a comprehensive criminological study on crime in the field of sports. In the course of the research, content analysis, documentary method and general scientific methods were used, such as comparison, analysis and synthesis, statistical and specifically sociological methods, as well as deductive method. The results of the study showed that the criminal policy and the current criminal legislation in the field of sports cause well-founded criticism of scientists, lawyers, and athletes, primarily for its inefficiency.

Research on contour feature extraction method of multiple sports images based on nonlinear mechanics

Abstract This article solves the issue of long extraction time and low extraction accuracy in traditional moving image contour feature extraction methods. Here authors have explored deformable active contour model to research the image processing technology in scientific research and the application of multiple sports and the method. A B-spline active contour model based on dynamic programming method is proposed in this article. This article proposes a method of using it to face image processing and extracting computed tomography (CT) image data to establish a three-dimensional model. The Lyapunov exponent, correlation dimension and approximate entropy of the nonlinear dynamics algorithm were used to extract the features of eight types of motor imagination electroencephalogram (EEG) signals. The results show that the success rate of pose reconstruction is more than 97% when the contour extraction quality is relatively ideal. The method is also robust to image noise, and the success rate of pose reconstruction can reach 94% when the video image has large noise. The execution efficiency is sub-linear, which can basically meet the requirements of real-time processing in video-based human posture reconstruction. The proposed method has a low error rate in the calculation of curvature features, effectively reduces the time for extracting contour features of moving images, and improves the accuracy of feature information extraction.

Sports Imaging of COVID-19: A Multi-Organ System Review of Indications and Imaging Findings.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in December 2019 in Wuhan, China. Although coronavirus disease-19 (COVID-19) affects every population group, the sports community and athletes require special consideration of the effects on cardiovascular, musculoskeletal, neurologic, and respiratory systems. A comprehensive understanding of imaging indications, findings, and features of COVID-19 supports appropriate imaging utilization and effective patient management and treatment. To review the spectrum of sports imaging in COVID-19 infection, organ system manifestations, vaccine effects, and complications in recreational and competitive athletes. Narrative review. Levels 4 and 5. Based on a PubMed database search, studies describing the imaging findings of COVID-19 infection, organ system manifestations, vaccine effects, and complications in recreational and competitive athletes were included. On March 11, 2020, World Health Organization officially declared COVID-19 a global pandemic. As of May 9, 2022, more than 515 million confirmed cases of COVID-19 were reported globally. While the multisystem effects of COVID-19 are incompletely understood, the role of imaging in diagnosing, monitoring, and prognosticating active disease, long-term effects, and complications is evolving. In the respiratory system, imaging plays an important role in diagnosing, characterizing, and monitoring pulmonary COVID-19 infections, barotrauma, and COVID-19-associated chronic pulmonary opacities and fibrotic-like lung changes. Ultrasonography, computed tomography, and magnetic resonance imaging aid in the timely diagnosis of ischemic, embolic, and thrombotic peripheral and central cardiovascular events, including deep venous thrombosis, pulmonary embolism, myocarditis, and stroke. COVID-19-associated musculoskeletal and peripheral nervous system manifestations include rhabdomyolysis and myonecrosis, plexus and peripheral neuropathies, Guillain-Barré syndrome, and shoulder injury related to vaccine administration. In athletes, COVID-19 infections and associated effects on cardiovascular, musculoskeletal, neurologic, and respiratory systems require special consideration. With the increasing understanding of the multisystem effects of COVID-19, the role of imaging in diagnosing, monitoring, and prognosticating active disease, long-term effects, and complications is evolving. A comprehensive understanding of imaging indications, COVID-19 imaging features, and organ system effects aids in appropriate imaging utilization and effective patient management and treatments.

Research on Automatic Tracking of Marking Points in Sports Image Sequences Based on Machine Learning

The article aims at dynamically fusing sports images to obtain the constraint items of the edge highlight model. At the same time, we combine the RGB feature decomposition technology to extract the feature mark point features. The article combines the steady-state matching technology to complete the automatic tracking of the landmark points of the sports image sequence. Preliminary application results show that this method has low requirements on the experimental environment, strong robustness, and high recognition rate. It can not only be used for human motion analysis, but also has great application potential for automatic tracking of moving targets in other free backgrounds.

Framework Design of Sports Image Analysis System Based on Player Behavior Information

Obtaining the data and information urgently needed by coaches and athletes through the processing of visual continuous images of sports is the most effective means and method in the current sport’s technical analysis. The sports image photography framework is an important tool for transforming the two-dimensional coordinates of sports technology images into three-dimensional space coordinates. The article proposes a calibration algorithm suitable for the two-plane calibration frame. The calculation is simpler than the DLT algorithm, and it is easy to program. The experimental results show that the system has good tracking effect of moving image key frames, high comprehensiveness, low redundancy and high recall rate.

Sports Image Decomposition Strategy Based on Moreau Envelope and Depth Recovery

Sports image decomposition technology is utilized broadly in different fields, and the technologies of sports image action identification situated on sports picture transformation technologies may be suitable. This paper utilizes the Moreau envelope and depth recovery for sports image decomposition strategy, an order of work such as a collection of sports image characteristic distillation, and action identification must be achieved in beginning and started with texture functions as well as various relevant functions. And both algorithms have to be utilized to finish the sports picture-oriented sports action identification technology at the lowest time expense. For the improvement of the latest sports image industry form, which is also strongly developed, the people’s affection for sports image is gaining as powerful and creates an improvement of sports image industry still achieving a lot of advantages. The parameters recognition rate and accuracy are compared with various techniques. The proposed methods are effective to achieve the perfect sports image decomposition.

The image of sport in the work of V.S. Vysotsky

Relevance. Art, being a form of cognition of life, sport, as a kind of game and spectacle had a theme of its research. Painting, literature, cinematography, using the specific means of their language, created a multicolored palette of sports life, portraits of outstanding athletes. Art lives in the atmosphere of its time, which determines the perception of sport, its historical dynamics, and social status. In the history of national culture, there was a peculiar era that received the official name - the thaw. In the history of national culture, there was a peculiar era that received the official name - the thaw. An iconic figure was the theater and film actor, poet, bard V.S. Vysotsky, in whose work sport occupied an important place. The article is an attempt to analyze the image of the sport, created by V.S. Vysotsky. The attention of the poet and singer to the psychological side of sports is noted, the importance of his images in the process of training future special-ists in the field of sports is emphasized.

The Praxiological Model of the Integrated Sports Concept in the Republic of Moldova

The article describes important elements of the Integrated Concept of Sport in the Republic of Moldova, focused on elements of good governance, protection of minors, fight against doping and corruption. Sport is a field that contributes substantially to sustainable development and economic growth of a state, ensuring an added value in its gross domestic product and the insertion of the specialists in the field on the labor market. National sports organizations are responsible for ensuring good governance in the reference field, its integrity in order to continuously improve the public's confidence in the positive values of sport and to increase the quality of life with its support. Moreover, ensuring good governance in national sport is dictated by the respect for the principle of autonomy and compliance with the legal framework of sports organizations (regulations, instructions, methodologies, etc.). Thus, good governance must "ensure the proper observance and regulation of the field through the principles of efficient, transparent, ethical and democratic management, sports diplomacy, fair play, participatory management, processes and structures with the participation of stakeholders" European Parliament Resolution of 2 February 2017 on an integrated approach to sport policy: good governance, accessibility and integrity 2016/2143 (INI). Good governance is needed to meet the challenges of sport and the legal framework of the European Union. Doping and corruption in sport, identified at national and European level, lead to the creation of an inadequate image of sport. Also, respect and protection of human rights, especially of minors, must be national principles of the rule of law. In this context, we can assert that the elaboration of the praxiological model of the Integrated Concept of sport at national level can strengthen the adjustment directions through modifications / proposals to the local legal framework that regulates the reference field in consensus with the European one.