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Title

Nonlinear Temporal Modeling for Motion-based Video Overviewing

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Published in Proceedings of the 3rd International Workshop on Content-Based Multimedia Indexing, CBMI'03. Rennes (France) - Sept. 22-24 - . 2003
Abstract This paper presents a method for video collection overviewing based the dynamic content of the scenes. In an unsupervised context, our approach relies on the nonlinear temporal modeling of wavelet-based motion features directly estimated from the image sequence. Based on SVM-regression, the nonlinear model is able to learn the behavior of the motion descriptors along the temporal dimension and to catch useful informations of the dynamic content. A similarity measure associated to the temporal model is then defined. It allows to compare video segments according to motion descriptors and thus defines a high-dimensional feature space where the video sequences under investigation are projected. The Curvilinear Component Analysis algorithm is finally used to map the feature space onto a 2D space. This operation enables us to display the video collection and gives an overview of the content according to motion features.
Keywords Nonlinear temporal modelingMotion-based video overviewingDynamic contentMotion descriptorVideo collectionHigh-dimensional feature spaceMotion featureImage sequenceTemporal model2d space feature spaceVideo sequenceVideo segmentApproach reliesSimilarity measureCurvilinear component analysis algorithmwavelet-based motion featureUnsupervised contextTemporal dimensionNonlinear modelUseful information
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Research groups Computer Vision and Multimedia Laboratory
Viper group
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BRUNO, Eric, MARCHAND-MAILLET, Stéphane. Nonlinear Temporal Modeling for Motion-based Video Overviewing. In: Proceedings of the 3rd International Workshop on Content-Based Multimedia Indexing, CBMI'03. Rennes (France). [s.l.] : [s.n.], 2003. https://archive-ouverte.unige.ch/unige:47726

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Deposited on : 2015-03-06

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