Structure analysis of soccer video with domain knowledge and hidden Markov models
作者: Lexing XiePeng XuShih-Fu ChangAjay DivakaranHuifang Sun
作者单位: 1Department of Electrical Engineering, Columbia University, New York, NY, USA
2Mitsubishi Electric Research Labs, Murray Hill, NJ, USA
刊名: Pattern Recognition Letters, 2004, Vol.25 (7), pp.767-775
来源数据库: Elsevier Journal
DOI: 10.1016/j.patrec.2004.01.005
关键词: Sports video analysisSoccer videoHidden Markov modelsDynamic programmingVideo syntax
原始语种摘要: Abstract(#br)In this paper, we present statistical techniques for parsing the structure of produced soccer programs. The problem is important for applications such as personalized video streaming and browsing systems, in which videos are segmented into different states and important states are selected based on user preferences. While prior work focuses on the detection of special events such as goals or corner kicks, this paper is concerned with generic structural elements of the game. We define two mutually exclusive states of the game, play and break based on the rules of soccer. Automatic detection of such generic states represents an original challenging issue due to high appearance diversities and temporal dynamics of such states in different videos. We select a salient feature set...
全文获取路径: Elsevier  (合作)
影响因子:1.266 (2012)