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P. Li, F. Chaumette. Image cues fusion for contour tracking based on particle filter. In Int. Workshop on Articulated Motion and Deformable Objects, AMDO'04, J.F. Perales, B.A. Draper (eds.), Lecture Notes in Computer Science, Volume 3179, Pages 99-107, Palma de Mallorca, Spain, September 2004.

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Particle filter is a powerful algorithm to deal with non-linear and non-Gaussian tracking problems. However the algorithm relying only upon one image cue often fails in challenging scenarios. To overcome this, the paper first presents a color likelihood to capture color distribution of the object based on Bhattacharry coefficient, and a structure likelihood representing high level knowledge regarding the object. Together with the widely used edge likelihood, the paper further proposes a straightforward image cues fusion for object tracking in the framework of particle filter, under assumption that the visual measurement of each image cue is independent of each other. The experiments on real image sequences have shown that the method is effective, robust to illumination changes, pose variations and complex background


Francois Chaumette

BibTex Reference

   Author = {Li, P. and Chaumette, F.},
   Title = {Image cues fusion for contour tracking based on particle filter},
   BookTitle = {Int. Workshop on Articulated Motion and Deformable Objects, AMDO'04},
   editor = {Perales, J.F. and Draper, B.A.},
   Volume = {    3179},
   Pages = {99--107},
   Series = {Lecture Notes in Computer Science},
   Address = {Palma de Mallorca, Spain},
   Month = {September},
   Year = {2004}

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