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Proceedings Paper

Hierarchical video summarization for medical data
Author(s): Xingquan Zhu; Jianping Fan; Ahmed K. Elmagarmid; Walid G. Aref
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Paper Abstract

To provide users with an overview of medical video content at various levels of abstraction which can be used for more efficient database browsing and access, a hierarchical video summarization strategy has been developed and is presented in this paper. To generate an overview, the key frames of a video are preprocessed to extract special frames (black frames, slides, clip art, sketch drawings) and special regions (faces, skin or blood-red areas). A shot grouping method is then applied to merge the spatially or temporally related shots into groups. The visual features and knowledge from the video shots are integrated to assign the groups into predefined semantic categories. Based on the video groups and their semantic categories, video summaries for different levels are constructed by group merging, hierarchical group clustering and semantic category selection. Based on this strategy, a user can select the layer of the summary to access. The higher the layer, the more concise the video summary; the lower the layer, the greater the detail contained in the summary.

Paper Details

Date Published: 19 December 2001
PDF: 12 pages
Proc. SPIE 4676, Storage and Retrieval for Media Databases 2002, (19 December 2001); doi: 10.1117/12.451110
Show Author Affiliations
Xingquan Zhu, Purdue Univ. (United States)
Jianping Fan, Univ. of North Carolina/Charlotte (United States)
Ahmed K. Elmagarmid, Purdue Univ. (United States)
Walid G. Aref, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 4676:
Storage and Retrieval for Media Databases 2002
Minerva M. Yeung; Chung-Sheng Li; Rainer W. Lienhart, Editor(s)

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