关键词: 目标跟踪, 粒子滤波, 多特征融合, 粒子集自适应调整

Abstract: To improve the real-time and robustness performance of particles filter algorithm for tracking vision objects, an adaptive particle filter tracking method based on multi-feature fusion is proposed. The proposed method uses the color and structural features to present the interested target. These features are integrated in the frame of particle filter, and the weights of particles are calculated by this integration, in order to conquer the distractions from the target deformation and the complex background. Meanwhile, particle number is calculated dynamically according to the tracking accuracy, and the particle-set is also adjusted adaptively, in order to promote the quality of particle and reduce its quantity, and then the cost of calculation is reduced. The experimental results show that the average of each frame’s operation time of the proposed method is nearly half of classic hybrid algorithm, and the proposed method is of higher robustness.

Key words: object tracking, particle filter, multi-features fusion, particle-set being adjusted adaptively