Improvement of likelihood in particle filter for interactive color tracking

In this paper, we propose an idea that is improving method of likelihood in particle filter. Following methods have been proposed as the previous method by us. First, an user is able to select a tracking object as a region of interest (ROI) in a single image from video sequence. Then, color feature in the ROI are used as a color of interest (COI). During the tracking, two color components of HSV color space are automatically chosen by the color feature analysis in each particle. However, in the previous method, values of likelihood is fixed. If values of particles are in range of the COI, the likelihood value is 1.0. Otherwise particles are set in 0.2 as the likelihood value. This value is fixed regardless of the distance from COI. To improve accuracy of tracking, we propose the method that the likelihood is dynamically changed depending on the distance from COI. In our experiments, the proposed method is compared with the previous method. As results, the accuracy of the proposed method is better than the previous method.