Immune particle filter algorithm for target tracking based on histograms of color and oriented gradient

Focusing on fails to track with standard particle filters when object and background have similar color and object is occluded, a new algorithm of immune particle filter object tracking based on histograms of color and oriented gradient is proposed. Color histogram is the global description of targets in color image, histogram of oriented gradient contains some construction information. The gradient feature is added, the poor performance of only one feature is improved when the environment changes. In addition, the proposed immune optimization algorithm improved the diversity of particles, especially the decline of the impact of sample impoverishment when occlusion occurs. Experimental results show that the proposed method is able to track the object stably, when one of the features loses discrimination ability for tracking. It is simple and suitable to be applied to deal with tracking problems in complex scene.