Stereo matching of color images using differential invariants

In this paper, we present a new method for matching points in stereoscopic, uncalibrated color images. Our approach works on point primitives and consists first in using a point characterization based on differential invariants, defined until now for gray value images. Then we define additional invariants of first order, exploiting color information. The characterization obtained is invariant to orthogonal transformations of the image. In addition, we make it robust to affine transformations of illumination. Second, we propose a simple and efficient scheme for point matching, using our differential characterization. Finally, we present matching and epipolar geometry results obtained on complex scenes. The results clearly show the pertinence of our approach. We are able to match points robustly and rapidly, using only derivatives till first order