Utility-based summarization of home videos Truong, Ba Tu and Venkatesh, Svetha 2007, Utility-based summarization of home videos, in MMM'07 : Advances in multimedia modeling : Proceedings of the 13th International Multimedia Modeling Conference, Springer-Verlag Berlin Heidelberg, Berlin, Germany, pp. 505-516, doi: 10.1007/978-3-540-69423-6_49. Attached Files Name Description MIMEType Size Downloads Title Utility-based summarization of home videos Author(s) Truong, Ba Tu Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Conference name International Multimedia Modeling Conference (13th : 2007 : Singapore, Singapore) Conference location Singapore, Singapore Conference dates 9-12 Jan. 2007 Title of proceedings MMM'07 : Advances in multimedia modeling : Proceedings of the 13th International Multimedia Modeling Conference Editor(s) Cham, Tat-Jen Cai, Jianfei Dorai, Chitra Rajan, Deepu Chua, Tat-Seng Publication date 2007 Conference series International Multimedia Modeling Conference Start page 505 End page 516 Total pages 12 Publisher Springer-Verlag Berlin Heidelberg Place of publication Berlin, Germany Keyword(s) home video static summarization identity count identity recognition sense of space activity recognition Summary The 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. ISBN 9783540694212 3540694218 Language eng DOI 10.1007/978-3-540-69423-6_49 Field of Research 089999 Information and Computing Sciences not elsewhere classified Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2007, Springer-Verlag Berlin Heidelberg Persistent URL http://hdl.handle.net/10536/DRO/DU:30044835 Document type: Conference Paper Collection: School of Information Technology Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges   Connect to conference webpage Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 01 May 2012, 11:01:22 EST Fri, 04 May 2012, 13:39:03 EST Fri, 04 May 2012, 13:44:48 EST Sat, 17 Jun 2017, 03:11:07 EST Sat, 21 Oct 2017, 02:02:15 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 298 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Tue, 01 May 2012, 11:01:22 EST

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