Personalized Sports Video Customization for Mobile Devices

Author(s):  
Chao Liang ◽  
Yu Jiang ◽  
Jian Cheng ◽  
Changsheng Xu ◽  
Xiaowei Luo ◽  
...  
Keyword(s):  
Author(s):  
D. Tjondronegoro

Sports video is very popular thanks to its in-progress (live) information and entertainment values. Many users are motivated to access sports video using mobile devices, since they often cannot watch the game on their sofa due to a busy life and inability to cope with lengthy games. The current generation of mobile video services has only focused on supporting the when and where consumers can watch their favorite sports matches. Since total control over playback and content is neglected, users often have to settle with low-quality videos and static content, which have been pre-processed. This limitation slows down the progress towards an era in which users are comfortable using their mobile devices to enjoy sports broadcasts while gaining total control over what they can watch at their most convenient time and place. In this article, we will describe a mobile video system which offers users full support over the when, where and how they want to watch sports video. The main new features offered are: (1) non-linear navigation within single and/or multiple documents; (2) customizable and personalized summaries; (3) multimodal access and video representation.


2011 ◽  
Vol 18 (2) ◽  
pp. 72-84 ◽  
Author(s):  
Jungong Han ◽  
Dirk Farin ◽  
Peter de With

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hui Wang ◽  
Meng Wang ◽  
Peng Zhao

Sports video is loved by the audience because of its unique charm, so it has high research value and application value to analyze and study the video data of competition. Based on the background of football match, this paper studies the football detection and tracking algorithm in football game video and analyzes the real-time image of real-time mobile devices in sports video augmented reality. Firstly, the image is preprocessed by image graying, image denoising, image binarization, and so on. Secondly, Hough transform is used to locate and detect football, and according to the characteristics of football, Hough transform is improved. Based on the good performance of SIFT algorithm in feature matching, a football tracking algorithm based on SIFT feature matching is proposed, which matches the detected football with the sample football. The simulation results show that the improved Hough transform can effectively detect football and has good antijamming performance. And the designed football tracking algorithm based on SIFT feature matching can accurately track the football trajectory; therefore, the football detection and tracking algorithm designed in this paper is suitable for real-time football monitoring and tracking.


Author(s):  
Jian Qin ◽  
Jun Chen ◽  
Zheng Wang ◽  
Jiyang Zhang ◽  
Xinyuan Yu ◽  
...  
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document