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Conference papers

Image cues fusion for contour tracking based on particle filter

P. Li 1 François Chaumette 1
1 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : 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.
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Submitted on : Monday, January 12, 2009 - 1:53:20 PM
Last modification on : Thursday, January 20, 2022 - 4:20:33 PM
Long-term archiving on: : Tuesday, June 8, 2010 - 7:31:38 PM


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P. Li, François Chaumette. Image cues fusion for contour tracking based on particle filter. Int. Workshop on Articulated Motion and Deformable Objects, AMDO'04, 2004, Palma de Mallorca, Spain. pp.99-107. ⟨inria-00352027⟩



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