Pretty much all of my research aims at highly robust and efficient algorithms that make a difference in practically relevant, real-world scenarios. I therefore actively develop and publish open-source code to make my developments available to a broad community. Most of it is disseminated through my github channel
Below is a list of my open-source releases with download and documentation links. You are more than welcome to contribute (preferrably through github's pull-request mechanism).
Precompiled Windows Matlab mex-library: Download here!
Precompiled Mac OSX Matlab mex-library: Download here!

OpenGV is a C++ library for solving geometric computer vision problems. It contains efficient implementations of absolute-pose, relative-pose, triangulation, and point-cloud alignment methods for the calibrated case. All problems can be solved for central or non-central cameras, and embedded into a random sample consensus or nonlinear optimization scheme. The library is relying on the adapter pattern, and thus may easily be included into other projects. It furthermore contains a Matlab interface and a full benchmark kit for testing and comparing algorithms against each other. All my geometric computer vision algorithms are contained within this library (including my P3P solver).
Please cite the following paper if using the library:
L. Kneip, P. Furgale, "OpenGV: A unified and generalized approach to real-time calibrated geometric vision", Proc. of The IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China. May 2014.
More references are included on the documentation page!
License: GPL

polyjam is a C++ library for setting up algebraic geometry problems and generating efficient C++ code that solves the underlying polynomial systems of equations. It notably does so by applying the theory of Groebner bases. polyjam is the driving force behind OpenGV, as all my geometric computer vision algorithms that involve the solution of multivariate polynomial equation systems contain solvers generated by this library. Problems of such form may be required in many engineering disciplines, which is why the tools provided through this library are of broad applicability. Please read the documentation for in-depth user instructions.
Documentation: Instructions are now contained in the package
License: FreeBSD

This is the original Matlab/C++ code for my P3P algorithm. It is the state-of-the-art solution to the absolute pose problem, which consists of computing the position and orientation of a camera given 3 image-to-world-point correspondences. Execution time in C++ lies in the order of a microsecond on common machines. The algorithm requires normalized image points, and therefore requires the camera to be intrinsically calibrated. Note that the algorithm is also contained in OpenGV.

A modification of the BRIEF descriptor permitting an online rotation of the extraction pattern (useful if some knowledge of the orientation around the camera principle axis is given). The interface is OpenCV compatible, and extended by two further functions:
setRotationCase( double rotation ): sets a rotated pattern from the base pattern
freezeRotationCase(): transfers the rotated pattern to the base pattern