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ICIP
2007
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Mining Auxiliary Objects for Tracking by Multibody Grouping

14 years 5 months ago
Mining Auxiliary Objects for Tracking by Multibody Grouping
On-line discovery of some auxiliary objects to verify the tracking results is a novel approach to achieving robust tracking by balancing the need for strong verification and computational efficiency. However, the applicability and effectiveness of this approach highly depend on how to reliably validate the motion correlation between the target and the auxiliary objects so as to estimate the motion model. In this paper, we extend the algorithm of mining auxiliary objects for tracking by incorporating multibody grouping to detect the motion correlation and estimate the motion model, which imposes more general motion correlation constraints. The proposed method discovers the auxiliary objects that exhibit strong affine motion correlation and estimates the closed-form affine models. The proposed tracking algorithm shows good performance in real-world test sequences.
Ming Yang, Ying Wu, Shihong Lao
Added 21 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2007
Where ICIP
Authors Ming Yang, Ying Wu, Shihong Lao
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