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A novel image matching method in camera-calibrated system

机译:相机校准系统中的一种新型图像匹配方法

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A novel approach for matching points from two views in a camera-calibrated system is presented in this paper. The interest points are selected using epipolar gradient features. Then three local region invariant descriptors, together with similarity measures are proposed. These descriptors are constructed from binary-threshold gray histogram, sample statistics of the edge points’ epipolar gradients, and average intensities of points on the epipolar line, respectively, all image patches based. Similarity measures relative to the descriptors work in cascade. Experimental results demonstrate that our matching scheme is tolerant to image deformations due to changes of viewpoint and effects of perspective, and can find more corresponding points.
机译:本文介绍了一种用于从相机校准系统中的两个视图匹配点的新方法。使用eMIPOL梯度特征选择兴趣点。然后提出了三个本地区域不变的描述符,以及相似度量。这些描述符由二进制阈值灰度直方图,边缘点'eBipolar梯度的样本统计,以及ePipol线上的点的平均强度,所有基于图像斑块。相似性测量相对于描述符在级联中工作。实验结果表明,由于观点的变化和视角的影响,我们的匹配方案是耐受图像变形,并且可以找到更多的相应点。

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