Dense stereo fish-eye images using a modified hemispherical ASW algorithm.

Abstract

In this paper, we concentrate on dense estimation of disparities between fish-eye images without corrections. Because of the distortions, fish-eye images cannot be processed directly utilizing the classical adaptive support weight (ASW) method for perspective images. To address this problem, we propose a modified hemispherical ASW method in a hemispherical framework. First, 3D epipolar curves are calculated directly on a hemispherical model to deal with the problem that 2D epipolar curves cannot cover the whole image disc. Then, a modified ASW method with hemispherical support window and hemispherical geodesic distance is presented. Moreover, a three-dimensional epipolar distance transform (3DEDT) is proposed and fused into the matching cost to cope with the textureless region problem. The benefit of this approach is demonstrated by realizing the dense stereo matching for fish-eye images using a public fish-eye data set, for which both objectively evaluated as well as visually convincing results are provided.