WITHDRAWN: Time Series Analysis of Volleyball Spiking Posture Based on Quality-Guided Cyclic Neural Network

Zhang, Chuanchang; Tang, Huan; Duan, Zhigang

doi:10.1016/j.jvcir.2019.102681

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Each team attempts to ground a ball on the opposite team's court and to score points under the defined rules. So, detecting and analyzing the player activities [163][164][165], detecting play patterns and classifying tactical behaviors [166][167][168][169], predicting league standings [170], detecting and classifying spiking skills [171,172], estimating the pose of the player [173], tracking the player [174], tracking the ball [175], etc., are the major aspects of volleyball analysis. Predicting the ball trajectory [59] in a volleyball game by observing the motion of the setter player has been conducted.…”

Section: Volleyballmentioning

confidence: 99%

A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

2022

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Recent developments in video analysis of sports and computer vision techniques have achieved significant improvements to enable a variety of critical operations. To provide enhanced information, such as detailed complex analysis in sports such as soccer, basketball, cricket, and badminton, studies have focused mainly on computer vision techniques employed to carry out different tasks. This paper presents a comprehensive review of sports video analysis for various applications: high-level analysis such as detection and classification of players, tracking players or balls in sports and predicting the trajectories of players or balls, recognizing the team’s strategies, and classifying various events in sports. The paper further discusses published works in a variety of application-specific tasks related to sports and the present researcher’s views regarding them. Since there is a wide research scope in sports for deploying computer vision techniques in various sports, some of the publicly available datasets related to a particular sport have been discussed. This paper reviews detailed discussion on some of the artificial intelligence (AI) applications, GPU-based work-stations and embedded platforms in sports vision. Finally, this review identifies the research directions, probable challenges, and future trends in the area of visual recognition in sports.

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Section: Volleyballmentioning

confidence: 99%

A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

2022

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“…Volleyball arm stroke is the key to scoring. Tracking the image trajectory of volleyball arm stroke, combined with image processing technology for trajectory analysis, is of great significance to improve the accuracy of volleyball arm stroke [6,7]. In this case, how to effectively recognize the arm trajectory of volleyball players has become the main problem to be solved in this field.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Tracking Method of Volleyball Player’s Arm Hitting Image Based on D-P Algorithm

Qin

2021

Scientific Programming

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Aiming at the problems of poor image tracking effect, low precision, and long time in the process of image tracking of volleyball player’s arm hitting, a volleyball player's arm hitting image tracking method based on D-P algorithm is proposed. This paper analyzes the basic concept, basic principle, and basic equation of D-P algorithm and collects the arm stroke trajectory image of volleyball players under the three-dimensional visual model. Using wavelet multiscale decomposition method, the arm stroke trajectory of volleyball players is filtered, and the edge contour feature points of the arm stroke image of volleyball players are extracted. Using the gray histogram feature extraction method, the gray information of volleyball player's arm hitting trajectory image is enhanced. Combined with pixel adaptive enhancement technology, the key action feature points of volleyball player's arm hitting image trajectory are located. Based on D-P algorithm, the volleyball player's arm hitting image trajectory is adjusted and modified to realize the correct tracking of volleyball player's arm hitting image trajectory. The experimental results show that the trajectory tracking effect of volleyball player's arm hitting image is better, which can effectively improve the tracking accuracy and shorten the tracking time.

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Analysis of Future Income Forecast for Indonesian Tourism Industry – A Neural Network Research on Tourism Digital Economy

Hidayat

Mahardiko²,

Alaydrus

2021

IOP Conf. Ser.: Earth Environ. Sci.

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Information Technology (IT) is an enabler for Indonesian tourism industry. Before Covid-19 pandemic, the industry already felt the effect of IT. The pandemic changes the global industry situation. This paper presents mathematical model on the number of tourism start-up, the number of local and international tourists, and national Gross Domestic Product (GDP). The results of this study show that while there are problems because of Covid-19 pandemic in the following year, the future income of tourism industry shows steady growth. The model can be used by other industry for better analysis.

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WITHDRAWN: Time Series Analysis of Volleyball Spiking Posture Based on Quality-Guided Cyclic Neural Network

Cited by 3 publications

References 14 publications

A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

Trajectory Tracking Method of Volleyball Player’s Arm Hitting Image Based on D-P Algorithm

Analysis of Future Income Forecast for Indonesian Tourism Industry – A Neural Network Research on Tourism Digital Economy

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