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Stereo Matching with Global Edge Constraint and Occlusion Handling

机译:立体声匹配与全局边缘约束和遮挡处理

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In this paper, an effective constraint is proposed to leverage the stereo matching in early vision literature. Firstly, some particular edges are extracted to compose the new smooth constraint by categorizing the color edges into different groups. Then the optimal support windows can be established based on the proposed constraint. Finally, the disparity map would be estimated by using match propagation within the optimal support windows. Compared to the traditional window-based algorithms, our method is more effective to deal with the difficulties caused by the occluded regions or disparity discontinuities. We evaluated our algorithm with real stereo pair of images and the experimental results showed the good performance.
机译:在本文中,提出了一种有效的约束,以利用早期视觉文献中的立体声匹配。 首先,提取一些特定边缘来通过将彩色边沿分类为不同的组来撰写新的平滑约束。 然后可以基于所提出的约束来建立最佳支持窗口。 最后,将通过在最佳支持窗口内使用匹配传播来估计视差图。 与传统的基于窗口的算法相比,我们的方法更有效地处理由遮挡区域或差异不连续性引起的困难。 我们用真正的立体声对图像评估了我们的算法,实验结果表现出良好的性能。

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