In this paper, we present a novel framework for multiple vehicles tracking in traffic crossroad that formulate multi-target tracking as an optimization problem. We set the optimizing decision model of multi-vehicles tracking based on characteristics of vehicles and traffic crossroad. In our formulation the problem of error propagation can be avoided through cutting down the error of detector by rejecting the improper detecting points during the optimizing process. Several challenging datasets are employed to validate the accuracy and robustness of our approach. A series of experiment results has demonstrated that our method is able to handle partial or even complete occlusions and can hardly be influenced by variant scale object.

Date Published: 13 March 2013
PDF: 7 pages
Proc. SPIE 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing, 878303 (13 March 2013); doi: 10.1117/12.2010557

Published in SPIE Proceedings Vol. 8783:
Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)