Discriminant and Invariant Color Model for Tracking under Abrupt Illumination Changes

The output from a color imaging sensor, or apparent color, can change considerably due to illumination conditions and scene geometry changes. In this work we take into account the dependence of apparent color with illumination an attempt to find appropriate color models for the typical conditions found in outdoor settings. We evaluate three color based trackers, one based on hue, another based on an intrinsic image representation and the last one based on a proposed combination of a chromaticity model with a physically reasoned adaptation of the target model. The evaluation is done on outdoor sequences with challenging illumination conditions, and shows that the proposed method improves the average track completeness by over 22% over the hue-based tracker and the closeness of track by over 7% over the tracker based on the intrinsic image representation.