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Clustering-based analysis of semantic concept models for video shots

Koskela, Markus and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2006) Clustering-based analysis of semantic concept models for video shots. In: ICME 2006 - IEEE International Conference on Multimedia and Expo, 9-12 July 2006, Toronto, Canada.

Abstract
In this paper we present a clustering-based method for representing semantic concepts on multimodal low-level feature spaces and study the evaluation of the goodness of such models with entropy-based methods. As different semantic concepts in video are most accurately represented with different features and modalities, we utilize the relative model-wise confidence values of the feature extraction techniques in weighting them automatically. The method also provides a natural way of measuring the similarity of different concepts in a multimedia lexicon. The experiments of the paper are conducted using the development set of the TRECVID 2005 corpus together with a common annotation for 39 semantic concepts
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:entropy; feature extraction; multimedia systems; pattern clustering; video signal processing;
Subjects:Engineering > Signal processing
Computer Science > Multimedia systems
Computer Science > Digital video
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://dx.doi.org/10.1109/ICME.2006.262546
Copyright Information:Copyright © 2006 IEEE. Reprinted from ICME 2006 - IEEE International Conference on Multimedia and Expo. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Dublin City University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Funders:Irish Research Council for Science Engineering and Technology
ID Code:227
Deposited On:05 Mar 2008 by DORAS Administrator . Last Modified 08 Nov 2018 10:42
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