Hierarchical Disparity Estimation with Programmable 3D Hardware

Christopher Zach
VRVis Research Center
Application Area 2
A-8010 Graz
Austria

Abstract

This work presents an implementation of a hierarchical disparity estimation algorithm entirely executed on programmable 3D graphics hardware. In contrast to previous hardware based implementations of computational stereo algorithms, our method calculates disparities either for rectified stereo images or uncalibrated pairs of stereo images without known epipolar geometry. We exploit features of modern graphics hardware to search for correct disparity vectors efficiently. The hierarchical approach increases the speed and the robustness of the algorithm. Additionally, we use bidirectional matching to remove false matches. We observe up to 50 fps for input images with 256x256 pixels resolution on desktop graphics cards and up to 30 fps on mobile 3D hardware.