Motion Estimation from Range Images in Dynamic Outdoor Scenes

Abstract : Object-class independent motion estimation from range data is a challenging task. We present here a novel approach that is able to derive a dense motion field based on range images only. We propose to first segment the range image into segments using a recently proposed segmentation criterion. Motion is then estimated segment-wise with full 6 degrees of freedom. To that end, we introduce dynamic mapping, i.e. the accumulation of measurements for moving objects. We show experimentally that the approach is able to deliver a dense motion field which can then be used for object-class independent trajectory estimation.
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Communication dans un congrès
IEEE Int. Conf. on Robotics and Automation, May 2010, Anchorage, United States. 2010
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Contributeur : Thierry Fraichard <>
Soumis le : mercredi 2 février 2011 - 23:29:13
Dernière modification le : mercredi 11 avril 2018 - 01:52:29
Document(s) archivé(s) le : mardi 3 mai 2011 - 03:53:27

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  • HAL Id : inria-00562251, version 1

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Franck Moosmann, Thierry Fraichard. Motion Estimation from Range Images in Dynamic Outdoor Scenes. IEEE Int. Conf. on Robotics and Automation, May 2010, Anchorage, United States. 2010. 〈inria-00562251〉

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