Multi View Stereo 10 (MVS10)

MVS10 builds a dense reconstruction of a 3D scene from a set of pictures (taken with a camera in photo mode or extracted from a video). Its input is a nvm file which comes either from Structure from Motion 10 (SfM10) or VisualSFM : A Visual Structure from Motion System and the images. The nvm file contains the camera poses (location and orientation) as well as a sparse 3D reconstruction of the scene. MVS10 is loosely based upon "Bundled Depth-Map Merging for Multi-View Stereo" by Jianguo Li, Eric Li, Yurong Chen, Lin Xu, Yimin Zhang. MVS10 pairs selected images/cameras, computes the corresponding disparity maps, and merges them as best as possible.

If you go to the 3D Software page and download/extract ugosoft3d-10-x64.rar, you will find a manual for MVS10 called "mvs10_manual.pdf". The manual explains the workflow/pipeline of MVS10 and the parameters in "mvs10_input.txt", the input file needed by MVS10. In order to use MVS10, you need to run Structure from Motion 10 (SfM10) first.

The output of MVS10 is:
- A set of frames named duh_XX.jpg where XX varies from 01 to 11 that can be used to create an animated gif of the reconstructed 3D scene.
- A point cloud in ply format names duh.ply that describes the 3D scene which can be loaded and possibly meshed (I recommend using the Poisson method) in MeshLab.

Here are a few examples:

Set of 3 images (1280x720) extracted from a video taken with iphone4s.

Sparse 3D reconstruction obtained with SfM10.

Dense 3D reconstruction obtained with MVS10.

Set of 8 images (1280x720) extracted from a video taken with iphone4s.

Sparse 3D reconstruction obtained with SfM10.

Dense 3D reconstruction obtained with MVS10.

Set of 8 images (1080x1920) extracted from a video taken with iphone4s.

Sparse 3D reconstruction obtained with SfM10.

Dense 3D reconstruction obtained with MVS10.

Here's a tutorial video for MVS10:


The windows executable (guaranteed to be virus free) is available for free via the 3D Software Page.

Source code: MVS10 on github.