Fuzzy based foreground background discrimination for probabilistic color based object tracking

In the most of object tracking tasks dealing with partial occlusion is a challenging issue. Recently the use of color cue based on Monte Carlo tracking method and particle filtering is mostly considered to overcome the problem of partial occlusion and nonrigid motion. The proposed approach in this paper is based on using of sequential Monte Carlo and particle filtering for tracking. But in this method a special fuzzy based color model for object is employed. Then comparison of mean value of reference and candidate window in the proposed color space is utilized for tracking of objects. Some of the morphological operation is also used to provide a unit region for object location in the fuzzy based color space. Experimental results indicate that the algorithm is efficient in dealing with partial occlusion.