high performance computing on graphics processing units: hgpu.org

We propose an area-based local stereo matching algorithm that yields accurate disparity estimates, while achieving the real-time speed completely on the graphics processing unit (GPU). For a local stereo method, the key challenge is to decide an appropriate support window for the pixel under consideration. Our stereo method starts with computing an upright local cross adaptively for each anchor pixel, which defines a per-pixel support skeleton. Next, based on this compact local cross representation, we aggregate the matching costs in a shape adaptive full support region using two orthogonal integration steps. Approximating scene structures accurately, the proposed method is among the best-performing real-time stereo methods according to the benchmark Middlebury stereo evaluation. Additionally, our method is very easy to implement, memory efficient, and hence it is promising for many practical applications.