Semantic and structural analysis of TV diving programs

  • Authors:

  • Fei Wang;Jin-Tao Li;Yong-Dong Zhang;Shou-Xun Lin

  • Affiliations:

  • Institute of Computing Technology, The Chinese Academy of Sciences, Beijing 100080, P.R. China and Graduate School of the Chinese Academy of Sciences, Beijing 100039, P.R. China;Institute of Computing Technology, The Chinese Academy of Sciences, Beijing 100080, P.R. China;Institute of Computing Technology, The Chinese Academy of Sciences, Beijing 100080, P.R. China;Institute of Computing Technology, The Chinese Academy of Sciences, Beijing 100080, P.R. China

  • Venue:
  • Journal of Computer Science and Technology
  • Year:
  • 2004

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Abstract

Automatic content analysis of sports videos is a valuable and challenging task. Motivated by analogies between a class of sports videos and languages, the authors propose a novel approach for sports video analysis based on compiler principles. It integrates both semantic analysis and syntactic analysis to automatically create an index and a table of contents for a sports video. Each shot of the video sequence is first annotated and indexed with semantic labels through detection of events using domain knowledge. A grammar-based parser is then constructed to identify the tree structure of the video content based on the labels. Meanwhile, the grammar can be used to detect and recover errors during the analysis. As a case study, a sports video parsing system is presented in the particular domain of diving. Experimental results indicate the proposed approach is effective.