I have finally released my Structure-From-Motion Toolkit (SFMToolkit). So what can you do with it ? Let’s say you have a nice place like the one just bellow:

Place de la Bourse, Bordeaux, FRANCE (picture from Bing)

Well, now you can take a lot of pictures of the place (around 50 in my case):

And then compute structure from motion and get a sparse point cloud using Bundler:

Finally you have a dense point cloud divided in cluster by CMVS and computed by PMVS2:

You can also take a loot at the PhotoSynth reconstruction of the place with 53 pictures and 26 (without the fountain).

This is the SFMToolkit workflow:

SFMToolkit is composed of several programs:

• BundlerFocalExtractor : extract CCD width from Exif using XML database.
• BundlerMatcher : extract and match feature using SiftGPU.
• Bundler : http://phototour.cs.washington.edu/bundler/ created by Noah Snavely.
• CMVS : http://grail.cs.washington.edu/software/cmvs/ created by Yasutaka Furukawa.
• PMVS2 : http://grail.cs.washington.edu/software/pmvs/ created by Yasutaka Furukawa.
• BundlerViewer : Bundler and PMVS2 output viewer based on Ogre3D (OpenSource 3D rendering engine).

Download

As you can see this “toolkit” is composed of several open-source component. This is why I have decided to open-source my part of the job too. You can download the source code from the SFMToolkit github. You can also download a pre-compiled x64 version of the toolkit with windows scripting (WSH) for easier usage (but not cross-platform): SFMToolkit1.zip.

Help

If you need some help or just want to discuss about photogrammetry, please join the photogrammetry forum created by Olafur Haraldsson. You may also be interested by Josh Harle’s video tutorials, they are partially out-dated due to the new SFMToolkit but these videos are very good to learn how to use MeshLab.

Please go to the SFMToolkit page to get the latest version

In my previous post I have released my PhotoSynth Tookit but the PhotoSynth tile downloader wasn’t available yet. You can now download the picture of your Synth in HD using PhotoSynthTileDownloader1.zip. But please respect author’s copyright ! I have included a new confirmation dialog box that warn you about the Synth status (unlisted, public) but this is not shown in the video presentation of PhotoSynthTileDownloader.

BundlerMatcher

I have finally released BundlerMatcher, a feature extraction and picture matching tool built with SiftGPU. The main goal of this tool was to replace the slow matching step packaged with Bundler by a faster one using GPU without needing to modify Bundler’s code. You can download BundlerMatcher1.zip or checkout the code on my google code. Warning: this tool needs a 64bit windows OS (tested on 7 and vista) and a decent GPU. All my demos are available under MIT license but SiftGPU isn’t released under MIT so you should take a look at SiftGPU license.

OpenSynther

I’m proud to introduce OpenSynther which is under heavy development. The first goal of this tool is the same as BundlerMatcher: provide a faster matching engine for Structure from Motion tools. To achieve high performance it is coded in C++ and using both multi-core and GPU. Furthermore OpenSynther is using Surf instead of Sift and may in the future also compute the 3d reconstruction (as PhotoSynth does).

OpenSynther current feature list:

• Jpeg loading + Exif reading
• multi-threaded Surf feature extraction (based on OpenSurf & ParallelSurf)
• multi-threaded Surf feature matching (based on OpenSurf matching + Cuda GPU matching)
  • Quadratic complexity O(n²) with n number of pictures

OpenSynther TODO:

• multi-threaded Surf feature approximate matching (based on FLANN)
  • Linear complexity (hypothetical)
• integrate 3d reconstruction ?
  • using Bundler code or insight3D, both are using SBA.

Benchmarks

These benchmarks were done on an Intel Corei7 920 (8 cores @ 2.66Ghz) + Nvidia GTX 285. The pictures size were 1600×1200 (~2M pixels), I heard that it was the limit size at which PhotoSynth extract features (it can of course use bigger pictures but feature extraction are done at a max size of 2M pixels).

Note:

• Bundler: I had to reduce picture to 640×480, otherwise I got too many features (would be unfair).
• PhotoSynth: I didn’t take into account the time spent in tile creation.
• OpenSynther: in the future I may consider using GPUSurf for feature extraction.
• BundlerMatcher: to be fair with PhotoSynth I didn’t write the ascii key file (so in fact it’s slower).

Note:

• PhotoSynth: they did a very good job and managed to have a linear matching !
• OpenSynther: the GPU is in fact doing the most part of the job as you can see in the table below:

As you can see OpenSynther matching is in fact done by the GPU at 85%.