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Conference papers

Robust Real Time Tracking of 3D Objects

Lucie Masson 1 Michel Dhome 1 Frédéric Jurie 2
2 LEAR - Learning and recognition in vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : In this article the problem of tracking rigid 3D objects is addressed. The contribution of the proposed approach is an algorithm which combines: efficiency (i.e. the algorithm is designed before all to be real time using standard architecture), robustness (occlusions are allowed) and accuracy (sub-pixel accuracy is obtained). It is devoted to the tracking of 3D rigid objects, assuming that the 3D geometry as well as the texture of the surface is known. Such performances can be obtained through a two levels scheme: the core of the approach consists in an efficient 2D patch tracker whose results are combined robustly to compute the 3D object pose. This article provides experimental results proving the soundness of the proposed approach.
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Lucie Masson, Michel Dhome, Frédéric Jurie. Robust Real Time Tracking of 3D Objects. 17th IEEE International Conference on Pattern Recognition (ICPR '04), Aug 2004, Cambridge, United Kingdom. pp.252, ⟨10.1109/ICPR.2004.1333751⟩. ⟨inria-00548540⟩



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