colmap 操作流程

colmap 操作流程

此为视频笔记, 原视频来源于bilibili https://www.bilibili.com/video/BV135411G7sR?spm_id_from=333.1007.top_right_bar_window_custom_collection.content.click

1. 新建一个项目数据库文件，放在Project workplace文件夹下

2. 点击 Processing > Feature Extraction 进行特征提取参数，默认即可

3. 点击Processing > Feature matching 进行特征匹配，参数默认，时间会比特征提取长

4. 点击reconstruction > start reconstruction 进行 SfM 与 三角化建立稀疏点云，期间伴随着光束法平差（Bundle Adjustment）。重建的结果是稀疏点云（就是刚刚提取的特征点三角化后的三维坐标）和相机位姿恢复的示意图。可以把稀疏点云导出为.ply文件查看

5. 点击reconstruction>dense reconstruction 进入稠密重建步骤（如果你电脑没cuda到这一步之后就可以结束了）

6. 点击右上角select选择稠密重建项目保存的文件夹，可以在workplace下建一个dense文件夹来保存。

7. 点击Undistortion 进行图像的去畸变

8. 点击Stereo 进行密集匹配（过程漫长）。完成密集匹配后可以看到生成的深度图，colmap采用的是PatchMatch的倾斜窗口密集匹配算法。

9. 点击 Fusion 进行深度图融合生成稠密点云。可以导出稠密点云结果将其保存。

10. 这里有两个选项，Possion是泊松表面重建，Delaunay是狄洛尼三角网重建。

11. 结果需要在Meshlab上看，打开dense文件夹下的meshed-possion.ply文件。

colmap官网对于流程步骤的作用解释

Structure-from-Motion

Structure-from-Motion (SfM) is the process of reconstructing 3D structure from its projections into a series of images. The input is a set of overlapping images of the same object, taken from different viewpoints. The output is a 3-D reconstruction of the object, and the reconstructed intrinsic and extrinsic camera parameters of all images. Typically, Structure-from-Motion systems divide this process into three stages:

1.Feature detection and extraction
2.Feature matching and geometric verification
3.Structure and motion reconstruction

Multi-View Stereo

Multi-View Stereo (MVS) takes the output of SfM to compute depth and/or normal information for every pixel in an image.
Fusion of the depth and normal maps of multiple images in 3D then produces a dense point cloud of the scene.
Using the depth and normal information of the fused point cloud, algorithms such as the (screened) Poisson surface reconstruction can then recover the 3D surface geometry of the scene.