This paper presents a novel method for cost aggregation and occlusion handling for stereo matching. In order to estimate optimal cost, given a per-pixel difference image as observed data, we define an energy function and solve the minimization problem by solving the iterative equation with the numerical method. We improve performance and increase the convergence rate by using several acceleration techniques such as the Gauss-Seidel method, the multiscale approach, and adaptive interpolation. The proposed method is computationally efficient since it does not use color segmentation or any global optimization techniques. For occlusion handling, which has not been performed effectively by any conventional cost aggregation approaches, we combine the occlusion problem with the proposed minimization scheme. Asymmetric information is used so that few additional computational loads are necessary. Experimental results show that performance is comparable to that of many state-of-the-art methods. The proposed method is in fact the most successful among all cost aggregation methods based on standard stereo test beds.
Bibliographical noteFunding Information:
Manuscript received April 30, 2007; revised April 13, 2008. First published June 17, 2008; last published July 11, 2008 (projected). This work was supported in part by MEST, MKE, and MOLAB through the fostering project of the Lab of Excellency, and in part by the MKE, Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA [IITA-2008-(C1090-0801-0011)]. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Hassan Foroosh.
All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design