Particle filter targets tracking by fusing multiple features

Under complex environment, it is impossible to track target accurately by only a feature. Thus, a novel object tracking method was proposed by fusing multi-feature in the framework of particle filter. Using Fisher linear discriminative theory, some discriminative features were extracted from the set of features, by which target could be distinguished from background very well and target appearance was kept consistent on time domain. Then, all discriminative features were fused adaptively in the framework of particle filter to track target. Experiment results show the proposed method is robust to occlusion and environmental change with high precision.