A novel color-context descriptor and its applications

This paper presents a new descriptor for object categorization and pedestrian identification applications. One of the main drawbacks of shape-context descriptor is its vulnerability and distinctness to color images. We propose a spherical descriptor that simultaneously adopts the spatial and color information as a discriminative representation. Based on the descriptor, this paper also contributes a bagof- features framework to pedestrian identification for video surveillance. In contrast to the previous works, the proposed scheme does not require background subtraction stage. Thus the potential problems, such as the susceptibility to shadows and highlights from the background subtraction procedure, are avoided. Experiments validate the discriminant power of the proposed descriptor in object categorization on COIL- 100 database and pedestrian identification in surveillance videos.