Tracking by Combining Photometric Normalization and Color Invariants According to their Relevance

Abstract

This paper addresses the problem of robust feature points tracking by using specific color invariants -robust to specular reflections, lighting changes and to some extent to color lighting changes-when they are relevant and photometric normalization in the opposite case. Indeed, most color invariants become noisy or irrelevant for low saturation and/or low intensity. They can even make tracking fail. Combining them with luminance information yields to a more performant tracking, whatever the lighting conditions are. A few experiments on real image sequences prove the efficiency of this procedure.