Automatic scene detection for advanced story retrieval

  • Authors:

  • Songhao Zhu;Yuncai Liu

  • Affiliations:

  • Institute of Image Process and Pattern Recognition, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China;Institute of Image Process and Pattern Recognition, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

Browsing video scenes is just the process to unfold the story scenarios of a long video archive, which can help users to locate their desired video segments quickly and efficiently. Automatic scene detection of a long video stream file is hence the first and crucial step toward a concise and comprehensive content-based representation for indexing, browsing and retrieval purposes. In this paper, we present a novel scene detection scheme for various video types. We first detect video shot using a coarse-to-fine algorithm. The key frames without useful information are detected and removed using template matching. Spatio-temporal coherent shots are then grouped into the same scene based on the temporal constraint of video content and visual similarity of shot activity. The proposed algorithm has been performed on various types of videos containing movie and TV program. Promising experimental results shows that the proposed method makes sense to efficient retrieval of video contents of interest.