Jinjun Wang, Changsheng Xu, Chng Eng Siong, K. Wan, Q. Tian
{"title":"Automatic replay generation for soccer video broadcasting","authors":"Jinjun Wang, Changsheng Xu, Chng Eng Siong, K. Wan, Q. Tian","doi":"10.1145/1027527.1027535","DOIUrl":null,"url":null,"abstract":"While most current approaches for sports video analysis are based on broadcast video, in this paper, we present a novel approach for highlight detection and automatic replay generation for soccer videos taken by the main camera. This research is important as current soccer highlight detection and replay generation from a live game is a labor-intensive process. A robust multi-level, multi-model event detection framework is proposed to detect the event and event boundaries from the video taken by the main camera. This framework explores the possible analysis cues, using a mid-level representation to bridge the gap between low-level features and high-level events. The event detection results and mid-level representation are used to generate replays which are automatically inserted into the video. Experimental results are promising and found to be comparable with those generated by broadcast professionals.","PeriodicalId":292207,"journal":{"name":"MULTIMEDIA '04","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"70","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MULTIMEDIA '04","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1027527.1027535","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 70
Abstract
While most current approaches for sports video analysis are based on broadcast video, in this paper, we present a novel approach for highlight detection and automatic replay generation for soccer videos taken by the main camera. This research is important as current soccer highlight detection and replay generation from a live game is a labor-intensive process. A robust multi-level, multi-model event detection framework is proposed to detect the event and event boundaries from the video taken by the main camera. This framework explores the possible analysis cues, using a mid-level representation to bridge the gap between low-level features and high-level events. The event detection results and mid-level representation are used to generate replays which are automatically inserted into the video. Experimental results are promising and found to be comparable with those generated by broadcast professionals.