Person re-identification using color name descriptor-based sparse representation

This paper presents a person re-identification algorithm using HSV color histogram matching and sparse representation. To continuously track a person who is captured by multiple cameras without overlapping regions, the person re-identification is essential. The proposed algorithm uses color information to recognize a person in a low resolution image. The proposed person re-identification algorithm consists of two steps: i) HSV color histogram matching and gallery reduction and ii) sparse representation matching using color name descriptor. The proposed algorithm minimizes unnecessary calculations and increases accuracy by reducing the number of candidates using HSV color histogram matching. In addition, it is invariant to occlusion and illumination variation using the sparse representation-based re-identification approach. As a results, it can be applied to a multiple camera-based video surveillance system for public security in airports and stores.