Feature-Based Stereo Matching Using Graph Cuts

In this paper, we present a novel feature point based stereo matching algorithm with global energy minimization. The initial disparity map is estimated by considering matching SURF key points between two images inside each homogeneous colour region by an adaptive box matching approach. Next, we improve the initial disparity map with a RANSAC based plane fitting technique which relies on accuracy of the pixel disparities inside the homogeneous colour regions. Finally, the disparity map is further enhanced by incorporating energy constraints on smoothness between neighbouring regions using graph cuts. The methodology is tested on Middlebury test set and the results indicates that the proposed method is compatible with the current state-of-the-art stereo matching algorithms while decreasing the overall computational effort in matching process using already available feature points.