Color constancy using shadow-based illumination maps for appearance-based person re-identification

Robust people re-identification is one of the most challenging task, and still an unsolved problem for several applications in video surveillance. A large number of approaches use colors as main features for object description, which are in fact important cues for re-identification. However, colors captured by a camera suffer from unknown and changing global and local illumination conditions in the scene. Thus, color constancy is an essential pre-condition for robust color-based person re-identification. In this paper we introduce a new approach for automated estimation and compensation of local illumination in the scene. The proposed approach allows for handling of multiple light sources in the scene, and to compensate backlight illumination simultaneously. Both are continuous problems with high relevance to practical use of color-based approaches in video surveillance.