Video scene segmentation using sequential change detection

  • Authors:
  • Zhenyan Li;Hong Lu;Yap-Peng Tan

  • Affiliations:
  • Nanyang Technological University, Singapore;Fudan University, Shanghai, P. R. China;Nanyang Technological University, Singapore

  • Venue:
  • PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part III
  • Year:
  • 2004

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Abstract

In content-based video analysis, commonly the first step is to segment a video into independent shots. However, it is rather inefficient to represent video using shot information, as one hour video may contain more than a hundred shots. To address this limitation, most recent work has focused on segmenting a video into scenes, each aggregated by consecutive shots that share similar visual properties or cover a same dramatic event. With the use of sequential change detection and the help of nonparametric density estimation, we propose a novel approach for video scene segmentation in this paper. Experimental results obtained from various test videos suggest that the proposed approach is promising.