The Community for Technology Leaders
2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (2004)
Washington, D.C., USA
June 27, 2004 to July 2, 2004
ISSN: 1063-6919
ISBN: 0-7695-2158-4
pp: 139
Timo Volkmer , RMIT University, Melbourne, Australia
S. M. M. Tahaghoghi , RMIT University, Melbourne, Australia
Hugh E. Williams , RMIT University, Melbourne, Australia
ABSTRACT
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.
INDEX TERMS
null
CITATION
Timo Volkmer, S. M. M. Tahaghoghi, Hugh E. Williams, "Gradual Transition Detection Using Average Frame Similarity", 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 09, no. , pp. 139, 2004, doi:10.1109/CVPR.2004.357
85 ms
(Ver 3.3 (11022016))