A fast graph cut algorithm for disparity estimation
Cheng-Wei Chou, Jang-Jer Tsai, Hsueh‐Ming Hang, Hung-Chih Lin · 2010
In this paper, we propose a fast graph cut (GC) algorithm for disparity estimation. Two accelerating techniques are suggested: one is the early termination rule, and the other is prioritizing the α-β swap pair search order. Our simulations show that the proposed fast GC algorithm outperforms the original GC scheme by 210% in the average computation time while its disparity estimation quality is almost similar to that of the original GC.