Stereo matching based on segmented B‐spline surface fitting and accelerated region belief propagation

Abstract

The authors propose a new stereo matching algorithm based on an iterative optimisation framework including bi‐cubic B‐spline surface fitting and accelerated region belief propagation (BP). They first compute the initial cost and disparity map by the adaptive support‐weight approach and then launch the iterative process in which the disparity space image is refined via the bi‐cubic B‐spline fitting and optimised via the accelerated region BP. Two innovations are contained in the algorithm: (i) disparity space image refinement based on segmented bi‐cubic B‐spline surface fitting; and (ii) an accelerated region message passing approach for BP. The algorithm is verified on the Middlebury benchmark and experimental results show the algorithm is effective and achieves the state‐of‐the‐art accuracy.