Document Type
Journal Article
RIS ID
31286
Citation
Bouttefroy, Philippe; Bouzerdoum, Abdesselam; Phung, Son Lam; and Beghdadi, Azeddine, 2009, Vehicle tracking using projective particle filter, in L. O''Conner (Eds.), Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, Genova, Italy: IEEE, 7-12.
http://ro.uow.edu.au/era/1698
Abstract
This article introduces a new particle filtering approach for object tracking in video sequences. The projective particle filter uses a linear fractional transformation, which projects the trajectory of an object from the real world onto the camera plane, thus providing a better estimate of the object position. In the proposed particle filter, samples are drawn from an importance density integrating the linear fractional transformation. This provides a better coverage of the feature space and yields a finer estimate of the posterior density. Experiments conducted on traffic video surveillance sequences show that the variance of the estimated trajectory is reduced, resulting in more robust tracking.