Although steady progress has been made in recent stereo algorithms, producing accurate results in the neighborhood of depth discontinuities remains a challenge. Moreover, among the techniques that best localize depth discontinuities, it is common to work only with a discrete set of disparity values, hindering the modeling of smooth, nonfronto-parallel surfaces. We propose to estimate scene structure as a set of smooth surface patches. The disparities within each patch are modeled by a spline, while the extent of each patch is represented by a pixelwise labeling of the source images. Disparities and extents are alternately estimated in an iterative, energy minimization framework. Segmentation is via graph cuts, aided by image gradients. Input images are treated symmetrically, and occlusions are addressed explicitly. Promising experimental results are presented.
Michael H. Lin, Carlo Tomasi