MultimediaSystems-04 - Multimedia Systems 10: 98115 (2004)...

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Digital Object Identifer (DOI) 10.1007/s00530-004-0142-7 Multimedia Systems 10: 98–115 (2004) Multimedia Systems Exploring video content structure for hierarchical summarization Xingquan Zhu 1 , Xindong Wu 1 , Jianping Fan 2 , Ahmed K. Elmagarmid 3 , Walid G. Aref 3 1 Department oF Computer Science, University oF Vermont, Burlington, VT 05405, USA 2 Department oF Computer Science, University oF North Carolina, Charlotte, NC 28223, USA 3 Department oF Computer Science, Purdue University, W. LaFayette, IN 47907, USA Published online: 15 September 2004 – c ± Springer-Verlag 2004 Abstract. In this paper, we propose a hierarchical video sum- marization strategy that explores video content structure to provide the users with a scalable, multilevel video summary. ±irst, video-shot- segmentation and keyFrame-extraction algo- rithms are applied to parse video sequences into physical shots and discrete keyFrames. Next, an aFfnity (selF-correlation) ma- trix is constructed to merge visually similar shots into clus- ters (supergroups). Since video shots with high similarities do not necessarily imply that they belong to the same story unit, temporal inFormation is adopted by merging temporally adjacent shots (within a specifed distance) From the super- group into each video group. A video-scene-detection algo- rithm is thus proposed to merge temporally or spatially corre- lated video groups into scenario units. This is Followed by a scene-clustering algorithm that eliminates visual redundancy among the units.A hierarchical video content structure with in- creasing granularity is constructed From the clustered scenes, video scenes, and video groups to keyFrames. ±inally, we in- troduce a hierarchical video summarization scheme by execut- ing various approaches at diFFerent levels oF the video content hierarchy to statically or dynamically construct the video sum- mary. Extensive experiments based on real-world videos have been perFormed to validate the eFFectiveness oF the proposed approach. Keywords: Hierarchical video summarization – Video con- tent hierarchy –Video group detection –Video scene detection – Hierarchical clustering 1 Introduction Owing to the decreased cost oF storage devices, higher trans- mission rates, and improved compression techniques, digi- tal videos are becoming available at an ever-increasing rate. Correspondence to : X. Zhu (e-mail: xqzhu@cs.uvm.edu) This research has been supported by the NSF under grants 9972883- EIA, 9974255-IIS, 9983248-EIA, and 0209120-IIS, a grant From the state oF Indiana 21 th Century ±und, and by the U.S. Army Research Laboratory and the U.S.Army Research OFfce under grant DAAD19- 02-1-0178. However, the manner in which video content is presented For access (such as browsing and retrieval) has become a chal- lenging task, both For video application systems and For users.
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This note was uploaded on 06/13/2011 for the course CAP 6412 taught by Professor Staff during the Spring '08 term at University of Central Florida.

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MultimediaSystems-04 - Multimedia Systems 10: 98115 (2004)...

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