Title :
Mining Auxiliary Objects for Tracking by Multibody Grouping
Author :
Yang, Ming ; Wu, Ying ; Lao, Shihong
Author_Institution :
Northwestern Univ., Evanston
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
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.
Keywords :
motion estimation; object detection; tracking; auxiliary object mining; motion correlation; motion estimation; multibody grouping; online discovery; robust tracking; Collaboration; Computational efficiency; Head; Motion analysis; Motion detection; Motion estimation; Object detection; Robustness; Target tracking; Testing; Visual tracking; auxiliary objects; belief propagation; multi-body grouping;
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2007.4379321