搜索资源列表
opencv17
- 简单的同时使用OPENGL和OPENCV的例子，能够根据云点图生成3d图像，对学习3d重建和立体视觉很有用。-A simple example using OPENGL and OPENCV can generate 3d image based on the cloud point of Figure 3d image,which is helpful to study 3d reconstruction and stereo vision 。
Sparse-point-matching
- 基于opencv的稀疏点匹配与重建（无图像校正）-Sparse point matching and reconstruction (no image correction)
sparse-points-and-matching
- 稀疏点匹配与重建（无图像校正），结合OpenCV开放-sparse points and matching
cvut_test
- 基于opencv的 稀疏点匹配与重建 opencv书籍配套经典代码 -Sparse points matching based on opencv opencv books supporting and rebuilding classic code
Image-_recon
- 完成两幅图像的稀疏点的匹配和重建，C++的编程环境，opencv函数库-Do two sparse points matching and reconstruction of the image, c++ programming environment, opencv function library
opencvtest
- 由双目立体视觉系统匹配到的点来计算物体的真实坐标，对三维物体进行三维重建。-The real coordinate by binocular stereo vision system matching to the point to calculate the object, 3D reconstruction of 3D objects.
123456
- 基于窗口的稀疏点匹配及三维重建，其中利用了图像校正，及Opencv中的相关函数和类库-Based on sparse point matching and reconstruction of the window, where the use of the image correction, and Opencv relevant functions and libraries
稀疏点匹配与重建
- 基于OpenCV的计算机视觉技术实现的稀疏点匹配与重建(Sparse point matching and reconstruction based on OpenCV computer vision technology)