LIBVISO2 15.04.2011

LIBVISO2 15.04.2011 summary

License: GPL
Price: $0
Platform: Windows All
File size: 3.2 MB
Updated: 2012-01-29
Download: 68
Publisher: Andreas Geiger

LIBVISO2 15.04.2011 screenshot

LIBVISO2 15.04.2011 description

LIBVISO2, also known as Library for Visual Odometry 2 is built to be a fast and cross-platform C++ library with MATLAB wrappers for computing the 6 DOF motion of a moving mono/stereo camera.
The stereo version is based on minimizing the reprojection error of sparse feature matches and is rather general (no motion model or setup restrictions except that the input images must be rectified and calibration parameters are known).
The monocular version is still very experimental and uses the 8-point algorithm for fundamental matrix estimation. It further assumes that the camera is moving at a known and fixed height over ground (for estimating the scale).
Due to the 8 correspondences needed for the 8-point algorithm, many more RANSAC samples need to be drawn, which makes the monocular algorithm slower than the stereo algorithm, for which 3 correspondences are sufficent to estimate parameters.
The most significant differences to LIBVISO1 are as follows:
· No dependencies on external libraries anymore
· Higher feature density (up to 15.000 feature matches)
· Feature matching speed-up of factor 10 (1.000 features take ~35 ms)
· Visual odometry speed-up of factor 100 (4 ms at 1.000 features)
· Also supports monocular egomotion estimation now
· Monocular scale estimated by assuming a fixed camera height over ground
· Features can be tracked over a short period of time
· Structure-from-Motion pipeline (3D reconstruction)

What's New in This Release:
· First version of libviso2 is available for download. Please note that this version is still very beta-ish, e.g., it has not been tested under Windows/MacOS or 32 bit systems. Your bugreports are highly appreciated. Also note that the 3d fusion part is not included yet. We will probably upload this part in a couple of weeks.

LIBVISO2 15.04.2011 keywords

feature  algorithm  version  monocular  8 point algorithm  monocular version  calibration parameters  fundamental matrix estimation  

LIBVISO2 15.04.2011 for Developers

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LIBVISO2 15.04.2011 Copyright

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