A Novel Tracking Features Selection Method Based on Genetic Algorithm
نویسندگان
چکیده
In this paper a novel tracking feature selection method is presented. Assuming the features that best discriminate between object and background are also best for tracking the object. A two-class variance ratio is employed to measure the discriminability. Genetic algorithm is used to optimize the different features combination to generate the best tracking feature. To demonstrate our proposed method, selected feature are combined with Kernel-based tracking method. Experimental results show that the proposed method can robustly tracking moving object in low discriminately background scenario.
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