{"title":"Player Trajectory Reconstruction from Broadcast Basketball Video","authors":"Liang-Hua Chen, Hsin-Wen Chang, Hsiang-An Hsiao","doi":"10.1145/3133793.3133801","DOIUrl":null,"url":null,"abstract":"To increase the performance of sport team, the tactics analysis of team from game video is essential. Trajectories of the players are the most useful cues in a sport video for tactics analysis. In this paper, we propose a technique to reconstruct the trajectories of players from broadcast basketball videos. We first propose a mosaic based approach to detect the boundary lines of court. Then, the locations of players are determined by the integration of shape and color visual information. A layered graph is constructed for the detected players, which includes all possible trajectories. A dynamic programming based algorithm is applied to find the trajectory of each player. Finally, the trajectories of players are displayed on a standard basketball court model by a homography transformation. In contrast to related works, our approach exploits more spatio-temporal information in video. Experimental results show that the proposed approach works well and outperforms some existing technique.","PeriodicalId":217183,"journal":{"name":"Proceedings of the 2nd International Conference on Biomedical Signal and Image Processing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Conference on Biomedical Signal and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3133793.3133801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
To increase the performance of sport team, the tactics analysis of team from game video is essential. Trajectories of the players are the most useful cues in a sport video for tactics analysis. In this paper, we propose a technique to reconstruct the trajectories of players from broadcast basketball videos. We first propose a mosaic based approach to detect the boundary lines of court. Then, the locations of players are determined by the integration of shape and color visual information. A layered graph is constructed for the detected players, which includes all possible trajectories. A dynamic programming based algorithm is applied to find the trajectory of each player. Finally, the trajectories of players are displayed on a standard basketball court model by a homography transformation. In contrast to related works, our approach exploits more spatio-temporal information in video. Experimental results show that the proposed approach works well and outperforms some existing technique.