The KITTI Vision Benchmark Suite

Method

Points and Lines based Stereo Visual Odomery [st] [PLSVO]

Submitted on 15 Feb. 2016 10:19 by
Ruben Gomez-Ojeda (Universidad de Malaga)

Running time:		0.20 s
Environment:		2 cores @ 2.5 Ghz (C/C++)

Method Description:

SVO system that employs both point and line
features with a non-linear optimization of the
reprojection distances.

Parameters:

LSD Lines
ORB Points

Latex Bibtex:

@inproceedings{Gomez2015,
author = {Gomez-Ojeda, Ruben and Gonzalez-
Jimenez, Javier},
booktitle = {Robotics and Automation (ICRA), 2016
IEEE International Conference on},
publisher = {IEEE},
title = {{Robust Stereo Visual Odometry through a
Probabilistic Combination of Points and Line
Segments}},
year = {2016}
}

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.