Stereo Matching Using Epipolar Distance Transform
Stereo Matching Using Epipolar Distance Transform
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DOI：
10.1109/tip.2012.2207393
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发表时间：
2012-10
影响因子：
10.6
通讯作者：
Qingxiong Yang;N. Ahuja
中科院分区：
文献类型：
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作者：
Qingxiong Yang;N. Ahuja
在本文中，我们提出了一个简单而有效的图像变换，称为核线距离变换，匹配低纹理区域。它将图像强度值转换为沿极线沿着的平面段内的相对位置，使得低纹理区域中的像素变得可区分。从理论上证明了该变换具有仿射不变性，因此变换后的图像可直接用于立体匹配。任何现有的立体算法都可以直接与变换后的图像一起使用，以提高低纹理区域的重建精度。在真实的室内和室外图像上的实验结果表明，该变换在低纹理区域匹配、关键点检测和低纹理场景描述方面是有效的。我们在Middlebury图像上的实验结果也证明了我们的变换对高度纹理化场景的鲁棒性。所提出的变换具有很大的优点，其计算复杂度低。它在配备1.8 GHz Core i7处理器的MacBook Air笔记本电脑上进行了测试，视频图形阵列大小的图像速度约为每秒9帧。
In this paper, we propose a simple but effective image transform, called the epipolar distance transform, for matching low-texture regions. It converts image intensity values to a relative location inside a planar segment along the epipolar line, such that pixels in the low-texture regions become distinguishable. We theoretically prove that the transform is affine invariant, thus the transformed images can be directly used for stereo matching. Any existing stereo algorithms can be directly used with the transformed images to improve reconstruction accuracy for low-texture regions. Results on real indoor and outdoor images demonstrate the effectiveness of the proposed transform for matching low-texture regions, keypoint detection, and description for low-texture scenes. Our experimental results on Middlebury images also demonstrate the robustness of our transform for highly textured scenes. The proposed transform has a great advantage, its low computational complexity. It was tested on a MacBook Air laptop computer with a 1.8 GHz Core i7 processor, with a speed of about 9 frames per second for a video graphics array-sized image.