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Title of Journal: Multimed Tools Appl

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Abbravation: Multimedia Tools and Applications

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Springer US

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DOI

10.1007/bf01136254

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ISSN

1573-7721

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A framework for unsupervised mesh based segmentati

Authors: Andreas Kriechbaum Roland Mörzinger Georg Thallinger
Publish Date: 2009/09/24
Volume: 50, Issue: 1, Pages: 7-28
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Abstract

Multimedia analysis usually deals with a large amount of video data with a significant number of moving objects Often it is necessary to reduce the amount of data and to represent the video in terms of moving objects and events Event analysis can be built on the detection of moving objects In order to automatically process a variety of video content in different domain largely unsupervised moving object segmentation algorithms are needed We propose a fully unsupervised system for moving object segmentation that does not require any restriction on the video content Our approach to extract moving objects relies on a meshbased combination of results from colour segmentation Mean Shift and motion segmentation by feature point tracking KLT tracker The proposed algorithm has been evaluated using precision and recall measures for comparing moving objects and their colour segmented regions with manually labelled ground truth data Results show that the algorithm is comparable to other stateoftheart algorithms The extracted information is used in a search and retrieval tool For that purpose a moving object representation in MPEG7 is implemented It facilitates high performance indexing and retrieval of moving objects and events in large video databases such as the search for similar moving objects occurring in a certain periodThe authors would like to thank Werner Haas Werner Bailer and Peter Schallauer as well as several other colleagues at JOANNEUM RESEARCH who provided valuable feedback The research leading to these results has received funding from the European Community’s Seventh Framework Programme FP7/20072013 under grant agreement n° 216465 ICT project SCOVIS

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