DT Template based Moving Object Tracking with Shape Information by Particle Filter

Robust and real-time object tracking of any objects is a challenging task. Particle filtering has been proven very successful for non-gaussian and non-linear estimation problems. This paper describes a new approach to improve the moving object tracking system with particle filter using shape similarity. The shape similarity between a template and estimated regions in the video sequences can be measured by their normalized cross-correlation of distance transformation. Our observation model of the particle filter is based on shape from distance transformed (DT) edge features. Template is created instantly by selecting any object in a video scene and updated in every frame. Experimental results have been offered to show the effectiveness of the proposed method. M. Z. Islam, C. Oh, J. Yang, C. Lee, DT Template based Moving Object Tracking with Shape Information by Particle Filter, 7th IEEE International Conference on Cybernetic Intelligent Systems (CIS 2008), pp. 127-132, Sep. 2008