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
@InProceedings{Teuliere10a,
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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