14 March 1995 Video browsing using clustering and scene transitions on compressed sequences
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This paper describes a new technique for extracting a hierarchical decomposition of a complex video selection for browsing purposes. The technique combines visual and temporal information to capture the important relations within a scene and between scenes in a video, thus allowing the analysis of the underlying story structure with no a priori knowledge of the content. We define a general model of hierarchical scene transition graph, and apply this model in an implementation for browsing. Video shots are first identified and a collection of key frames is used to represent each video segment. These collections are then classified according to gross visual information. A platform is built on which the video is presented as directed graphs to the user, with each category of video shots represented by a node and each edge denotes a temporal relationship between categories. The analysis and processing of video is carried out directly on the compressed videos. Preliminary tests show that the narrative structure of a video selection can be effectively captured using this technique.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Minerva M. Yeung, Minerva M. Yeung, Boon-Lock Yeo, Boon-Lock Yeo, Wayne H. Wolf, Wayne H. Wolf, Bede Liu, Bede Liu, } "Video browsing using clustering and scene transitions on compressed sequences", Proc. SPIE 2417, Multimedia Computing and Networking 1995, (14 March 1995); doi: 10.1117/12.206067; https://doi.org/10.1117/12.206067


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