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C. Teulière, E. Marchand, L. Eck. Using multiple hypothesis in model-based tracking. In IEEE Int. Conf. on Robotics and Automation, ICRA'10, Pages 4559-4565, Anchorage, Alaska, May 2010.

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Classic registration methods for model-based tracking try to align the projected edges of a 3D model with the edges of the image. However, wrong matches at low level can make these methods fail. This paper presents a new approach allowing to retrieve multiple hypothesis on the camera pose from multiple low-level hypothesis. These hypothesis are integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Experiments on simulated and real video sequences show the improvement in robustness of the resulting tracker


Eric Marchand

BibTex Reference

   Author = {Teulière, C. and Marchand, E. and Eck, L.},
   Title = {Using multiple hypothesis in model-based tracking},
   BookTitle = {IEEE Int. Conf. on Robotics and Automation, ICRA'10},
   Pages = {4559--4565},
   Address = {Anchorage, Alaska},
   Month = {May},
   Year = {2010}

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