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人们之所以能够看到深度，是因为，来自三维世界的不同视角。本程序尝试从一个2D图像映射并计算对应的3D的距离。-People have been able to see the depth, is because the three-dimensional world from different perspectives. This procedure attempts to map from a 2D image and calculate the corresponding 3D dista
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二维图像三维立体视差算法依据的文章是：
“Segment-Based Stereo Matching Using Belief Propogation and a Self-Adapting Dissimilarity Measure” by Klaus, Sormann, and Karner
主要步骤：
Getting Pixel Disparity
Filtering the Pixel Disparity
包含的文件：
demo.m, .#newrea
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双目立体匹配中获取图像对的视差图，可用于后续的三维重建工作。-Binocular stereo matching to get the image on the disparity map can be used for subsequent 3D reconstruction.
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matlab实现图像匹配的视差图，可以用于3D重建系统，机器视觉等领域。-Matlab image matching parallax figure, and can be used in 3 D reconstruction system, machine vision, etc
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此程序使用opencv计算相应图像对的视差并作出视差图，进而以之为基础进行图像的三维重建。-This program calculates the disparity and plots the depthimage using opencv. Therefore, reconstruct the stereo image.
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通过立体像对校正计算视差图，为3D重建和立体回复的基础。对OPENCV的学习有一定的帮助。-By stereo disparity map for correction calculation for 3D reconstruction and stereo reply foundation. OPENCV of learning for some help.
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改进后的OpenCV立体测距源码，可以在OpenGL中显示视差点云-The improved OpenCV 3D stereo distance measurement. Disparity 3D points data can be displayed with OpenGL
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OpenCV+OpenGL 双目立体视觉三维重建代码以及文档使用opencv进行立体匹配获取视差图，三角剖分使用opengl进行纹理贴图-OpenCV+OpenGL binocular stereo vision 3D reconstruction code and documents using OpenCV stereo matching to obtain disparity map, triangulation using opengl for texture mapping
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双目立体匹配一直是双目视觉的研究热点，双目相机拍摄同一场景的左、右两幅视点图像，运用立体匹配匹配算法获取视差图，进而获取深度图。而深度图的应用范围非常广泛，由于其能够记录场景中物体距离摄像机的距离，可以用以测量、三维重建、以及虚拟视点的合成等(Binocular stereo matching has always been a research hotspot in binocular vision. Binocular cameras take left and right view ima
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