2004 Conference on Computer Vision and Pattern Recognition Workshop (2004)
Washington, D.C., USA
June 27, 2004 to July 2, 2004
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2004.357
Timo Volkmer , RMIT University, Melbourne, Australia
S. M. M. Tahaghoghi , RMIT University, Melbourne, Australia
Hugh E. Williams , RMIT University, Melbourne, Australia
Segmenting digital video into its constituent basic semantic entities, or shots, is an important step for effective management and retrieval of video data. Recent automated techniques for detecting transitions between shots are highly effective on abrupt transitions. However, automated detection of gradual transitions, and the precise determination of the corresponding start and end frames, remains problematic. In this paper, we present a gradual transition detection approach based on average frame similarity and adaptive thresholds. We report good detection results on the TREC video track collections - particularly for dissolves and fades - and very high accuracy in identifying transition boundaries. Our technique is a valuable new tool for transition detection.
T. Volkmer, S. M. Tahaghoghi and H. E. Williams, "Gradual Transition Detection Using Average Frame Similarity," 2004 Conference on Computer Vision and Pattern Recognition Workshop(CVPRW), Washington, D.C., USA, 2004, pp. 139.