A new stereo matching algorithm is introduced that performs iterative refinement on the results of adaptive support-weight stereo matching. During each iteration of disparity refinement, adaptive support-weights are used by the algorithm to penalize disparity differences within local windows. Analytical results show that the addition of iterative refinement to adaptive support-weight stereo mat...

This paper presents a framework for considering both stereo cues and structural priors to obtain a geometrically representative depth map from a narrow baseline stereo pair. We use stereo pairs captured with a consumer stereo camera and observe that traditional depth estimation using stereo matching techniques encounters difficulties related to the narrow baseline relative to the depth of the s...

We investigate the stereo matching techniques for high dynamic range (HDR) image pairs. It is an emerging topic in computer vision and multimedia applications due to the availability of HDR image capture devices. The disparity computation will eventually take the stereo HDR input. In this work, three state-of-the-art stereo matching algorithms are modified and used to test the advantages of HDR...

In the last years, most dense stereo matching methods use evaluation on the Middlebury stereo vision benchmark datasets. Most recent stereo algorithms were designed to perform well on these close range stereo datasets with relatively small baselines and good radiometric behaviour. In this paper, different matching costs on the Semi-Global Matching algorithm are evaluated and compared using the ...

This paper proposes a novel local stereo matching approach based on self-adapting matching window. We improve the accuracy of stereo matching in 3 steps. First, we integrate shape and size information, and construct robust minimum matching windows by applying a self-adapting method. Then, two matching cost optimization strategies are employed for handling both occlusion regions and image border...

This paper presents an algorithm for considering both stereo cues and structural priors to obtain a geometrically representative depth map from a narrow baseline stereo pair. We use stereo pairs captured with a consumer stereo camera and observe that traditional depth estimation using stereo matching techniques encounters difficulties related to the narrow baseline relative to the depth of the ...

Catadioptric Omni-Directional Stereo Vision (ODSV) technology is the combination of omni-directional imaging and stereo vision, which has wide application potentials on robot vision and large-scale video surveillance [1-4]. Fig.1 gives the framework of ODSV technology, which includes four major parts: the design of omni-directional stereo vision imaging system, unwarping of omni-directional ste...