Abstract
Symmetry is an important characteristic of vehicles and has been frequently used for detection tasks by many researchers. However, existing results of vehicle tracking seldom used symmetry property. In this paper, we will utilize the detected symmetry feature to design a proposal distribution of particle filter for vehicle tracking. The resulting proposal distribution can be closer to the true posterior distribution. Experimental results show that the use of symmetry information will obtain better tracking performance than the conventional color histogram-based particle filters.
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Liu, H., Sun, F. (2008). Particle Filter with Improved Proposal Distribution for Vehicle Tracking. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87732-5_48
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DOI: https://doi.org/10.1007/978-3-540-87732-5_48
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