关键词: Camshift, 特征融合, Harris角点, Bhattacharyya系数, 自适应

Abstract: In order to track moving targets in real time and effectively, in this paper, a new Camshift target tracking algorithm is proposed, in which corner features and color features are fused adaptively. The invariance of the corner is combined in this algorithm, and the kernel probability density estimation of the Mean-Shift algorithm is used to calculate the probability density function for each feature. Bhattacharyya coefficient is adopted as similarity measure function, then using the ratio of similarity to achieve adaptive fusion of corner and color features. The new probability density distribution and the Camshift tracking algorithm will be combined to achieve the target tracking. Simulation results show that the algorithm is better than traditional Camshift algorithm, and tracks object more accurately.

Key words: Camshift, feature fusion, Harris conner, Bhattacharyya coefficient, adaptive