Regularised Projection of an Image Domain Triangulation for Disparity Map Refinement

This is the authors' abstract. We don't add key points for this paper.

Most of the recent top-ranked stereovision algorithms are based on some oversegmentation of the stereo pair images. Each image segment is modelled as a 3D plane, transposing the stereovision problem into a 3-parameters plane estimation problem. Trying to find the set of planes that best fits the input data while regularising on 3D adjacent planes, a global energy is minimised using different optimisation strategies. The regularisation term is important as it enforces the reconstructed scene consistency. In this paper, we propose a disparity map refinement strategy based on a triangular mesh of the image domain. This mesh is projected along the rays of the camera, each triangle being modelled by a slanted plane. Considering triangles instead of free form superpixels, i.e. adding a geometrical constraint on the shape of segment boundaries, allows to formulate simpler regularisation terms that only involve the mesh vertex disparities in the computations. Different curvature regularisation terms of the literature are explored and a new one is proposed, with better properties with regard to the usual coplanarity assumption between adjacent planes. We demonstrate the performance gain of the proposed method compared to the popular Semi-Global Matching (SGM) algorithm.