Saturated Independent Color Coordinates for Image Alignment

Image alignment should be based on features that are robust with respect to phenomena such as global illumination changes, shading variations, and local highlights. While hue provides a natural degree of invariance to these phenomena, we show that it has several deficiencies in terms of gradient-based image alignment. To overcome these limitations, we introduce a 2D representation for hue that maintains a highly compressed representation for saturation. This allows the representation to model gray without sacrificing the desirable properties of hue. We show that our approach has a more consistent local domain of convergence when used for gradient-based alignment, and demonstrate its use in the context of a probabilistic motion-based tracker.