12 January 2018 An improved three-dimension reconstruction method based on guided filter and Delaunay
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Binocular stereo vision is becoming a research hotspot in the area of image processing. Based on traditional adaptive-weight stereo matching algorithm, we improve the cost volume by averaging the AD (Absolute Difference) of RGB color channels and adding x-derivative of the grayscale image to get the cost volume. Then we use guided filter in the cost aggregation step and weighted median filter for post-processing to address the edge problem. In order to get the location in real space, we combine the deep information with the camera calibration to project each pixel in 2D image to 3D coordinate matrix. We add the concept of projection to region-growing algorithm for surface reconstruction, its specific operation is to project all the points to a 2D plane through the normals of clouds and return the results back to 3D space according to these connection relationship among the points in 2D plane. During the triangulation in 2D plane, we use Delaunay algorithm because it has optimal quality of mesh. We configure OpenCV and pcl on Visual Studio for testing, and the experimental results show that the proposed algorithm have higher computational accuracy of disparity and can realize the details of the real mesh model.
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Yilin Liu, Yilin Liu, Xiu Su, Xiu Su, Haitao Liang, Haitao Liang, Huaiyuan Xu, Huaiyuan Xu, Yi Wang, Yi Wang, Xiaodong Chen, Xiaodong Chen, } "An improved three-dimension reconstruction method based on guided filter and Delaunay", Proc. SPIE 10620, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology, 106201D (12 January 2018); doi: 10.1117/12.2295058; https://doi.org/10.1117/12.2295058

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