C++ source code and datasets from my PhD research are now online

License

Download

Works in Linux, using gcc and the Netbeans ID for c++. May work in Windows (Windows/VS solution files are not currently maintained).

You need svn to get the latest version (or TortoiseSVN in Windows). svn might need to be told if you use a proxy.

BoWSLAM currently only works in Linux. Important Additional instructions here.

Linux: Use this command to check out a copy into a folder called workspace. Hit enter if asked for a password.

svn co https://open.grcnz.com/svn/point-stereo/trunk/workspace workspace

Windows: Right-click in explorer, select SVN Checkout... Enter the following url and hit ok:

https://open.grcnz.com/svn/point-stereo/trunk/workspace

Try the latest revision first, revision 1069 may work on older systems (with boost 1.39.0 or earlier).

Browse Source

https://open.grcnz.com/svn/point-stereo/trunk/workspace/

Or download revision 958 including all code, libraries and binaries (gcc 4.4, some bugs in BaySAC fixed since then)

Pre-requisites:

Features

BaySAC (and RANSAC and PROSAC and SimSAC and WaldSAC) for Essential Matrix estimation and Homography estimation. Topdown refinement of solution. Nonlinear refinement of E on hypothesis sets found by RANSAC. Example...

Fast 5-point Essential Matrix estimation and refinement.

Estimate Homography and decompose into translation, rotation, plane-normal (Levenberg-Marquardt)

Bag-of-Words library: Real-time performance and dynamic retraining. Supports 10k+ images. Fast pairwise correspondences.

K-medoids clustering.

Real-time mosaicing (generates a locally accurate seamless mosaic in real-time. Does not generate a globally accurate mosaic.)

Install

See License_and_Installation_Readme.txt. To use one simple function just copy the relevent code. To build libraries:

Install in Linux

Make sure include files and libraries for boost, Eigen, and OpenCV (if needed) are visible to gcc. If Eigen is not visible then make a symlink to it in your checkout dir: ln -s PATH_TO_YOUR_EIGEN_DIR Eigen

Either:

Open in Netbeans 7.0.

or

The makefiles supplied are generated by Netbeans. E.g. cd util; make will build libutil.a with debugging info, etc. Building BoWSLAM (cd BoWSLAM; make) will also build all libraries. Use make CONF=Release for optimised build.

It may also work in the latest Eclipse CDT (use Import Existing Project function, or create a new workspace.)

Install in Windows

Visual Studio 2008 (open ransac_bow_vision_lib.sln)
Visual Studio 2005 (open ransac_bow_vision_lib_VC2005.sln)

Make sure OpenCV, boost, Eigen header and library paths are set in the VC++ Directories

Binaries

The repository is not stable as I keep fixing bugs--it is easiest to get bug fixes using svn.
Download revision 958 including all code, libraries and binaries (gcc 4.4) **now out of date**

You can use the Bag-of-Words code from any programming language under Windows

Datasets

Four datasets are available via my google docs account (too large to put here). To download them please email me ( ) and I will provide access. Most are low framerate, fairly high resolution and from a single camera, and some have GPS ground truth (as NMEA data or in an openoffice spreadsheet) and camera calibration data.

• Aerial images for mosaicing: A sequence of 1610 aerial colour images sized 800x533 captured from a Canon SLR camera on a microlight over Motueka, NZ. Includes farmland, roads, shoreline, forest and urban areas. No GPS. Sample...
• Suburban dataset for Single Camera SLAM: 3864 greyscale images captured at 640x426 from a Canon 400D SLR camera, at 2.8Hz. 2.5km looping trajectory around suburban Christchurch, including pedestrians and vehicles. Sample...
• Helmetcam dataset for Single Camera SLAM: 2996 greyscale images sized 640x320 from a mountin bike helmet cam. Features poor light, motion blur, low-grade (low cost) optics, rapid, erratic 6DOF motion. Sample...
• Aerial images for mosaicing: A sequence of 1115 640x480 colour images captured at 2Hz from a Canon SLR camera on a UAV over Antarctic ice sheets. No GPS, few strong features. Sample...

Parameter documentation

Documentation for all parameters is online here. Some headers are documented, e.g. ransac.h for BaySAC, E estimation, H estimation.

Coming soon

1) Seperate out clustering functionality (CLARA k-medoids)

2) More examples and documentation :-)

Known issues

BoWSLAM has additional requirements (and does not work reliably with gcc versions 4.4 or earlier, or early versions of boost)

K-medoids has hard-coded limit of 450 data-points in Windows, and stack allocation will fail with more than about 1000 in Linux.