3D descriptor for people re-identification

In this paper we propose a new 3D descriptor for people re-identification using depth cameras. The descriptor is based on a 3D cylindrical grid that stores color variations with angle and height. A robust comparison method is also presented. This method ignores variations in brightness and contrast of descriptors obtained at possibly different locations. However it retains the ability to distinguish between different colors (e.g red vs. blue) or luminance patterns. Extensive results on three different scenarios are presented and prove the validity of the approach. The data sets used have been publicly released.