使用提供的图像和示例进行 OpenCV 3D 重建
我正在尝试使用 OpenCV 示例文件从立体配置执行 3D 表面重建。我用 2 个网络摄像头创建了一个立体摄像头。 我已经使用stereo_calib.cpp（ https://code.ros.org/trac/opencv/browser/trunk/opencv/samples/cpp/stereo_calib.cpp?rev=4086 ）并使用stereo_match生成点云。 .cpp（https://code.ros.org /trac/opencv/browser/trunk/opencv/samples/c/stereo_match.cpp?rev=2614 ）。使用 MeshLab 打开的结果点云根本不像原始场景 ( http:// img707.imageshack.us/i/snapshot01u.png/ ）。
我在这里缺少什么？
重新创建的步骤：
stereo_calib.cpp（在图像所在的同一文件夹中，没有参数，因此假定为默认值）
stereo_match left01.jpg right01.jpg -i insides.yml -e extrinsics.yml -p cloud.asc
在 MeshLab 上导入 cloud.asc
谢谢
I am trying to perform a 3D surface reconstruction from a stereo configuration with OpenCV example files. I have created a stereo camera from 2 web cams.
I have obtained the calibration parameters using stereo_calib.cpp ( https://code.ros.org/trac/opencv/browser/trunk/opencv/samples/cpp/stereo_calib.cpp?rev=4086 ) and generated a point cloud with stereo_match.cpp ( https://code.ros.org/trac/opencv/browser/trunk/opencv/samples/c/stereo_match.cpp?rev=2614 ). The resulting point cloud, opened with MeshLab doesn't resemble the original scene at all ( http://img707.imageshack.us/i/snapshot01u.png/ ).
What am I missing here?
Steps to recreate:
stereo_calib.cpp (on the same folder where the images are, with no arguments so it assumes default)
stereo_match left01.jpg right01.jpg -i intrinsics.yml -e extrinsics.yml -p cloud.asc
import cloud.asc on MeshLab
Thanks
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您发布的描述和图像没有提供太多信息。但根据我的 3D 重建经验，外部或内部参数似乎不正确。
因此，您的校准出了问题。您必须获得两个相机的内在校准以及相机之间的外部校准。
有很多涉及 3D 重建和立体主题的优秀文献。其中最重要的一本是“多视图几何”一书理查德·哈特利和安德鲁·齐瑟曼。
The description and the image you've posted do not give a lot of information. But from my experience with 3D reconstruction it seem to be that the extrinsic or intrinsic parameters are not correct.
Thus, something had gone wrong with your calibration. You have to get the intrinsic calibration of both cameras and the extrinsic between your cameras.
There is a lot of good literature covering the topic of 3D reconstruction and stereo. One of the most important of them is the book "Multiple View Geometry" from Richard Hartley and Andrew Zisserman.