A Target Tracking Method Based on Particle Filter and Multi-feature Fusion

Color histogram is a common modeling method when the particle filter is used in target tracking. But the color histogram contains only the color in-formation of the image, and the scope of application is limited. The spatial histogram contains both color and space information for the image, which overcomes many disadvantages of color histogram. And due to the weak robustness of single target tracking, this paper proposes a target tracking algorithm based on Quantum Genetic Algorithm (QGA) multi-feature fusion. Using the Quantum Genetic Algorithms to decide weighting coefficients. The method overcomes the problem of weak robustness by a single feature and poor integration of features. Experimental results show that the proposed method greatly improves the robustness of target tracking.