Abstract
In a video surveillance network, it is always required to track and recognize people when they move through the environment. This paper presents a novel re-identification method for multiple-people using feature selection with sparsity. By using the multipleshot approach, each of appearance models is created in this method. The human body is divided into five parts form which the features of color, height, gradient were extracted respectively. Our appearance model is represented by linear regression method. Experimental results show that our appearance model is robust and attain a high precision rate and processing performance.
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