Optimizing Synchronization of Tennis Professional League Live Broadcast Based on Wireless Network Planning

Tang, Kai; Huo, Lian-Juan

doi:10.1155/2021/8732115

Cited by 4 publications

(5 citation statements)

References 13 publications

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“…Tang and Huo used wireless network planning to improve the synchronization of tennis professional league live broadcasts. The results of the experiments show that the synchronization optimization method has good synchronization, high resolution, short response time, and good detection effect [4]. The impact of online advertising in promoting the Nigerian Professional Football League was investigated by Anorue et al (NPFL).…”

Section: Related Workmentioning

confidence: 99%

Chinese Professional Basketball League Using Mobile Computing and Big Data Technology

Yan

Liu

2022

Wireless Communications and Mobile Computing

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The impact of big data technology on the Chinese Men’s Professional Basketball League (CBA) is studied in this study. With the growth of the CBA league in recent years, teams from the western region have emerged. Although there is a trend of “multipolarization” in the competition pattern, it overall depicts a situation in which the east is strong and the west is weak. In addition, the method of recruiting foreign aid workers has improved over time, as has the foreign aid system. The number of foreign aids has increased from one in 1995 to a high of 47, and the quality of foreign aid has improved over time. This not only strengthens the club team, but it also has a significant impact on the CBA league’s competition patterns. The basic factors that affect the changes in the competition pattern are institutional factors, coaching factors, star player factors, foreign aid factors, regional economic factors, reserve talent factors, team style factors, player security factors, and so on, according to research and analysis of the CBA league’s development and changes. Six teams have won the CBA league championship in its 22 seasons. The Bayi and Guangdong teams each won eight times, accounting for more than 70% of the total number of championships.

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Section: Related Workmentioning

confidence: 99%

Chinese Professional Basketball League Using Mobile Computing and Big Data Technology

Yan

Liu

2022

Wireless Communications and Mobile Computing

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“…Where 1 i = , 2, 3, 1 denotes the jumping stance, 2 denotes the hip spreading stance, 3 denotes the stomaching stance, () i p and () i q denote the eigenangle vectors of the corresponding stances, (1) d  is the weighted Euclidean distance between the jumping eigenangle of the stance to be tested and the corresponding standard jumping stance eigenangle. (2) d  is the weighted Euclidean distance between the stance jerk eigenangle and the corresponding standard stance jerk eigenangle, (3) d  is the weighted Euclidean distance between the stance tuck eigenangle and the corresponding standard tuck eigenangle. n denotes the number of eigenangles, and () i j  denotes the weight of the j th eigenangle of stance i [29][30].…”

Section: Action Matching Algorithmmentioning

confidence: 99%

“…Tennis is a sport of strength, explosive force, and sensitivity coordination, which can make tennis players enjoy the game and bring infinite fun at the same time. With the increasing standardization of tennis teaching in colleges and universities, the importance of tennis teaching in colleges and universities is also increasing, and physical education teachers should pay more attention to the necessity of tennis technical training and implement the tennis technical practice in the actual teaching work [1][2]. In the teaching and practice of tennis technology, the improvement of practical efficiency can help students improve their skills, and the rational use of tennis training strategies can play a good role [3].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of tennis technical movement training strategy in colleges and universities under the background of big data technology

Huang,

Liu,

Pan

2023

Applied Mathematics and Nonlinear Sciences

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This paper first explains the tennis technical action representation and matching technology, using the Euler angle method to represent the coordinates of the tennis action gesture, realizing the deconstruction of the action gesture through the gesture-solving algorithm, and then using the weighted Euclidean distance to match the tennis gesture to the action. Secondly, we constructed the tennis technical movement training strategy for colleges and universities based on the task-driven teaching method, and gave the teaching experiment method to analyze the effectiveness of the strategy. Finally, the data was analyzed by examining the muscle characteristics of tennis technical movements and the teaching effect of task-driven teaching. The results showed that the maximal EMG integral value of the muscles was 32.91uV.s in the level 1 group and 87.91uV.s in the level 2 group, and the maximal angular velocity of the ankle-knee-hip joints was 645.23±189.42°/s and the minimum angular velocity of the hip joints was 461.87±115.08°/s in all the landing modes. 115.08°/s. The task-driven teaching method can effectively improve the students’ tennis learning and technical level and enhance the quality of tennis technical teaching in colleges and universities.

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“…The scheme first establishes a three-dimensional detection target model, extracts the background from the moving video image, uses the interframe difference elimination algorithm to extract, and predicts the target motion trajectory. Then, the scheme uses the Hilbert transform to analyze the phase difference characteristics of the foreground trajectory of the image and detects the missing points of the target [2]. To achieve higher processing efficiency and accuracy, Fan applies DL to object class detection.…”

Section: Related Workmentioning

confidence: 99%

Object Extraction of Tennis Video Based on Deep Learning

Huang

2022

Wireless Communications and Mobile Computing

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Moving target detection and tracking technology is the core technology in the field of computer vision. It integrates image processing, pattern recognition and intelligence, and artificial intelligence and automatic control are the keys to an intelligent video surveillance system. The method acquires video image signals through visible light or infrared sensors, performs digital image processing on the video images, detects moving targets, and then extracts moving targets for target recognition. Then, the moving target is predicted and tracked according to the image features and spatiotemporal features, and the contour shape, position, and motion trajectory of the target are obtained, which provides data support for subsequent tasks. This paper uses the convolutional neural network model HyperNet as the technical support to study the deep learning (DL) tennis video target extraction. The final experimental results show that the loss value of the loss function in the training process of this method is stably maintained between 1.5% and 2.5%, and the speed performance is also greatly improved. The number of boxes for extracting candidate regions is significantly reduced, the calculation time for each frame will not exceed 1.8 s, the orientation accuracy of target extraction is 96.32%, and the size accuracy is 91.05%.

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Optimizing Synchronization of Tennis Professional League Live Broadcast Based on Wireless Network Planning

Cited by 4 publications

References 13 publications

Chinese Professional Basketball League Using Mobile Computing and Big Data Technology

Chinese Professional Basketball League Using Mobile Computing and Big Data Technology

Analysis of tennis technical movement training strategy in colleges and universities under the background of big data technology

Object Extraction of Tennis Video Based on Deep Learning

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