Publication Details

Bouttefroy, P., Bouzerdoum, A., Phung, S. & Beghdadi, A. (2009). Vehicle tracking using projective particle filter. In L. O'Conner (Eds.), Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance (pp. 7-12). Genova, Italy: IEEE.


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.



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