Stereo matching using census cost over cross window and segmentation-based disparity refinement

Qingwu Li; Jinyan Ni; Yunpeng Ma; Jinxin Xu

doi:10.1117/1.JEI.27.2.023014

24 March 2018 Stereo matching using census cost over cross window and segmentation-based disparity refinement

Qingwu Li, Jinyan Ni, Yunpeng Ma, Jinxin Xu

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 2, 023014 (March 2018). https://doi.org/10.1117/1.JEI.27.2.023014

Abstract

Stereo matching is a vital requirement for many applications, such as three-dimensional (3-D) reconstruction, robot navigation, object detection, and industrial measurement. To improve the practicability of stereo matching, a method using census cost over cross window and segmentation-based disparity refinement is proposed. First, a cross window is obtained using distance difference and intensity similarity in binocular images. Census cost over the cross window and color cost are combined as the matching cost, which is aggregated by the guided filter. Then, winner-takes-all strategy is used to calculate the initial disparities. Second, a graph-based segmentation method is combined with color and edge information to achieve moderate under-segmentation. The segmented regions are classified into reliable regions and unreliable regions by consistency checking. Finally, the two regions are optimized by plane fitting and propagation, respectively, to match the ambiguous pixels. The experimental results are on Middlebury Stereo Datasets, which show that the proposed method has good performance in occluded and discontinuous regions, and it obtains smoother disparity maps with a lower average matching error rate compared with other algorithms.

Citation Download Citation

Qingwu Li, Jinyan Ni, Yunpeng Ma, and Jinxin Xu "Stereo matching using census cost over cross window and segmentation-based disparity refinement," Journal of Electronic Imaging 27(2), 023014 (24 March 2018). https://doi.org/10.1117/1.JEI.27.2.023014

Received: 6 November 2017; Accepted: 5 March 2018; Published: 24 March 2018

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