PMVS 30% Faster

I have integrated recent changes in PMVS from Nghia Ho and now PMVS is 30 % faster.

If you want test it by yourself you could reach the udpated source code in the GitHub repository
https://github.com/TheFrenchLeaf/CMVS-PMVS

Changelog :
Add changes from Nghia Ho http://nghiaho.com/
- memoize pow(2,X)
- Change GSL simplex to lmfit.

Open Source Photogrammetry cited in a paper

OpenSource Photogrammetry have been cited under the acronym OSP in the following paper :
M. Pierrot-Deseilligny, I. Cléry. APERO, an Open Source Bundle Adjusment Software for Automatic Calibration and Orientation of a Set of Images. Proceedings of the ISPRS Commission V Symposium, Image Engineering and Vision Metrology, Trento, Italy, 2-4 March 2011.

OpenSourcePhotogrammetry in ArcheOs

ArcheOS is the acronym of Archeological Operating System. It is a GNU/Linux live distribution built for archaeological aims. Actually a new version (4.0) based on Debian “Squeeze” is under development.

Alessandro Bezzi - Arc-Team s.n.c have done an excellent job to include my tools under this linux distribution (compatible also with debian/ubuntu). It have add an PYQT GUI :

And manage to get result like the following :

This result is a nice example of what open source community could manage ! Congrats to ArcheOs team !

At my turn I have now to integrate the change made by Alessandro to the toolkit on windows !

New package available for windows

I have just release as a christmas present a new packave that allow to use :
At your convenience :
 1. Bundler + PMVS2
Or
 2. Bundler + CMVS + PMVS2 on each computed cluster.

It could be launch with ease with two script in each case.
1. RunBundler.py + RunPMVS.py
2. RunBundler.py + RunCMVS.py

The archive is here and release with binary for windows 32 and 64 bits !

And for sure I have test the path 2. with a large dataset of 251 photos (2.1 * 2.8 MegaPixels) and I show you the results :

It looks pretty. Is'nt it ! A point cloud of 8 350 379 points !



3D reconstruction example

To advertise the upcoming release of our photogrammetry toolkit, I would like to post the result of 3D reconstruction from 5 photos of the old townhall in Market Harborough in England. Here is one of the photos:

All 5 photos can be downloaded from the toolkit homepage. The photos were taken by Andrew Ainsworth who also contributed to the project.

And finally, here is the result of 3D reconstruction with PMVS:

CMVS Compiles under Linux/Windows with CMake

CMVS now compiles fine with the CMake build system for windows and linux (32/64).

Next step will be to update the python photogrammetry package and make tutorials in order to provide a friendly access to "the pictures to 3D" platform.

If anyone is interested by giving some help, he is welcome !

Python Photogrammetry Toolbox

This project intend to create a python photogrammetry toolbox.

It provides an easy interface to run Bundler + Dense point cloud computation via PMVS2 and CMVS (as WIP).

The main drawbacks of Bundler is that people have to install cygwin to use it and windows.

The advantage of Python is that the scripting langage is multiplatform, so the same code will be ok to run Bundler and the other tools on windows, linux and mac ! No more cygwin... installation.

This project make the Sift detector from VLFeat library works with Bundler. So the toolchain is OpenSource from A to Z. Other modules could be plug into because of the modularity approach that have been choosen.

In a near future we could think in integrate a SIFTGpu matcher into the toolchain.

Running example :
Perform point cloud and camera calibration :

• $ RunBundler.py --photos="./examples/MyPhotos"

Perform dense 3D point cloud computation :

• $ RunPMVS.py --bundlerOutputPath="C:/temp/PreviousLineTempDirectoryPath"

Perform dense 3D point could computation by using Cluster 3D representation of the scene :

• $ RunCMVS.py --bundlerOutputPath="C:/temp/PreviousLineTempDirectoryPath"