The KITTI Vision Benchmark Suite

Method

CV4X - Stereo Visual Odometry [st] [cv4xv1-sc]

Submitted on 29 Jan. 2015 15:32 by
Mikael Persson (LIU::ISY::CVL)

Running time:		0.145 s
Environment:		GPU @ 3.5 Ghz (C/C++)

Method Description:

Robust Stereo Visual Odometry from Monocular
Techniques.

Multiscale Fast+Brief, local BA, late outlier
rejection. GPU Descriptor matching.
4 cores~ 50% load.

Parameters:

Detection Radius 5
Selection Radius 18
BA window 15+5
Many more... Specific set per submission available
on request.

Latex Bibtex:

@inproceedings{Persson2015IV,
Author = {M Persson and T Piccini and R
Mester and M Felsberg},
Title = {Robust Stereo Visual Odometry from
Monocular Techniques},
Booktitle = {IEEE Intelligent Vehicles Symposium},
Year = {2015}}

Detailed Results

From all test sequences (sequences 11-21), our benchmark computes translational and rotational errors for all possible subsequences of length (5,10,50,100,150,...,400) meters. Our evaluation ranks methods according to the average of those values, where errors are measured in percent (for translation) and in degrees per meter (for rotation). Details for different trajectory lengths and driving speeds can be found in the plots underneath. Furthermore, the first 5 test trajectories and error plots are shown below.