3D Human Video Retrieval: from Pose to Motion Matching

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dc.contributor.authorSlama, Rimen_US
dc.contributor.authorWannous, Hazemen_US
dc.contributor.authorDaoudi, Mohameden_US
dc.contributor.editorUmberto Castellani and Tobias Schreck and Silvia Biasotti and Ioannis Pratikakis and Afzal Godil and Remco Veltkampen_US
dc.date.accessioned2013-09-24T12:04:06Z
dc.date.available2013-09-24T12:04:06Z
dc.date.issued2013en_US
dc.description.abstract3D video retrieval is a challenging problem lying at the heart of many primary research areas in computer graphics and computer vision applications. In this paper, we present a new 3D human shape matching and motion retrieval framework. Our approach is formulated using Extremal Human Curve (EHC) descriptor extracted from the body surface and a local motion retrieval achieved after motion segmentation. Matching is performed by an efficient method which takes advantage of a compact EHC representation in open curve Shape Space and an elastic distance measure. Moreover, local 3D video retrieval is performed by dynamic time warping (DTW) algorithm in the feature space vectors. Experiments on both synthetic and real 3D human video sequences show that our approach provides an accurate shape similarity in video compared to the best state-of-the-art approaches. Finally, results on motion retrieval are promising and show the potential of this approach.en_US
dc.description.sectionheadersFull Papersen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-44-6en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3DOR/3DOR13/033-040en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectH.3.1 [Information storage and retrieval]en_US
dc.subjectContent Analysis and Indexingen_US
dc.subjectI.3.5 [Computer graphics]en_US
dc.subjectComputational Geometry and Object Modelingen_US
dc.title3D Human Video Retrieval: from Pose to Motion Matchingen_US
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