The KITTI Vision Benchmark Suite

Method

Library for Visual Odometry 2 (Monocular Version) [VISO2-M]
http://www.cvlibs.net/software/libviso

Submitted on 4 Apr. 2012 11:47 by
Andreas Geiger (MPI Tübingen)

Running time:		0.1 s
Environment:		1 core @ 2.5 Ghz (C/C++)

Method Description:

Uses sparse feature matching and the normalized 8
point algorithm in combination with RANSAC for
motion estimation. The ground plane is searched for
computing scale from known camera height over
ground.

Parameters:

Default parameters, except:
height = 1.7
pitch = -0.03
nms_n = 3
half_resolution = 0

Latex Bibtex:

@INPROCEEDINGS{Geiger2011IV,
author = {Andreas Geiger and Julius Ziegler and
Christoph Stiller},
title = {StereoScan: Dense 3d Reconstruction in
Real-time},
booktitle = {IV},
year = {2011},
month = {June},
address = {Baden-Baden, Germany}
}

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.