Adaptive edge-oriented shot boundary detection

  • Authors:

  • Don Adjeroh;M. C. Lee;N. Banda;Uma Kandaswamy

  • Affiliations:

  • Video and Image Processing Laboratory, Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV;Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin NT, Hong Kong;Video and Image Processing Laboratory, Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV;Video and Image Processing Laboratory, Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV

  • Venue:
  • Journal on Image and Video Processing
  • Year:
  • 2009

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Abstract

We study the problem of video shot boundary detection using an adaptive edge-oriented framework. Our approach is distinct in its use of multiple multilevel features in the required processing. Adaptation is provided by a careful analysis of these multilevel features, based on shot variability. We consider three levels of adaptation: at the feature extraction stage using locally-adaptive edge maps, at the video sequence level, and at the individual shot level. We show how to provide adaptive parameters for the multilevel edge-based approach, and how to determine adaptive thresholds for the shot boundaries based on the characteristics of the particular shot being indexed. The result is a fast adaptive scheme that provides a slightly better performance in terms of robustness, and a five fold efficiency improvement in shot characterization and classification. The reported work has applications beyond direct video indexing, and could be used in real-time applications, such as in dynamic monitoring and modeling of video data traffic in multimedia communications, and in real-time video surveillance. Experimental results are included.