关键词: 目标跟踪, 特征融合, 均值漂移, 粒子滤波

Abstract: When the moving object is occluded, or similar to background, it is hard to track the moving object. An optimize particle filter arithmetic based on adaptive features fusion mean shift method is proposed to solve this problem. This paper uses united histogram to describe the grayscale and gradient direction features of the object, adjusts features weight adaptively based on the features dependability of the object of prior picture. In particle filter theory it uses the improved mean-shift method to make particles of the particle filter to move towards estimated direction of maximal posterior kernel density of the target state, and designs a fusion observational model to improve the scene adaptability. The experimental result show that this algorithm can track military camouflage target reposefully where the color for both target and background are similar, and is robust for serious occlusion.

Key words: object tracking, features fusion, mean-shift, particle filter