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Edge Traction Stereo Matching Method Using RBf

机译:RBf的边缘牵引立体匹配方法

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摘要

For obtaining the precise and dense disparity map, a stereo matching method with occlusion detection using edge traction was presented, which is integrated with the area similarity and edge feature points in Radial Basis Function (RBF). Obtain the edge feature points by using LoG and their label sets of disparity to dividing the image region into feature and featureless sets. Area similarity, feature points and disparity smoothness are incorporated into error function of RBF. Relative reliable disparities of feature points restrict the disparity estimation of featureless points and decrease the possibility of forming mismatching illusion. Hierarchical Gaussians approach is imposed in this matching framework. Besides, we test the match values and the match conflict at sight lines to determine the occlusion area and avoid mismatching illusion. According the uniqueness constraint, whole high-density disparity map was obtained.
机译:为了获得精确而密集的视差图,提出了一种利用边缘牵引进行遮挡检测的立体匹配方法,该方法与径向基函数(RBF)中的区域相似度和边缘特征点集成在一起。通过使用LoG及其视差标签集来获取边缘特征点,以将图像区域分为特征集和无特征集。区域相似度,特征点和视差平滑度被合并到RBF的误差函数中。特征点的相对可靠视差限制了无特征点的视差估计,并降低了形成错配错觉的可能性。在此匹配框架中强加了高斯分层方法。此外,我们在视线上测试匹配值和匹配冲突,以确定遮挡区域并避免错配错觉。根据唯一性约束,获得了整个高密度视差图。

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