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Utility-based summarization of home videos
conference contribution
posted on 2007-01-01, 00:00 authored by B Truong, Svetha VenkateshSvetha VenkateshThe aim of this work is to devise an effective method for static summarization of home video sequences. Based on the premise that the user watching a summary is interested in people related (how many, who, emotional state) or activity related aspects, we formulate a novel approach to video summarization that works to specifically expose relevant video frames that make the content spotting tasks possible. Unlike existing approaches, which work on low-level features which often produce the summary not appealing to the viewer due to the semantic gap between low-level features and high-level concepts, our approach is driven by various utility functions (identity count, identity recognition, emotion recognition, activity recognition, sense of space) that use the results of face detection, face clustering, shot clustering and within cluster frame alignment. The summarization problem is then treated as the problem of extracting the set of key frames that have the maximum combined utility.
History
Event
International Multimedia Modeling Conference (13th : 2007 : Singapore, Singapore)Pagination
505 - 516Publisher
Springer-Verlag Berlin HeidelbergLocation
Singapore, SingaporePlace of publication
Berlin, GermanyPublisher DOI
Start date
2007-01-09End date
2007-01-12ISBN-13
9783540694212ISBN-10
3540694218Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2007, Springer-Verlag Berlin HeidelbergEditor/Contributor(s)
T Cham, J Cai, C Dorai, D Rajan, T ChuaTitle of proceedings
MMM'07 : Advances in multimedia modeling : Proceedings of the 13th International Multimedia Modeling ConferenceUsage metrics
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