The KITTI Vision Benchmark Suite

Method

Relative Monocular Camera Pose Estimation [RMCPE+GP]

Submitted on 17 Mar. 2015 09:46 by
Mohammad Hossein Mirabdollah (Paderborn university)

Running time:		0.39 s
Environment:		1 core @ 2.5 Ghz (C/C++)

Method Description:

The 7-point method relative camera position
estimation is modified to work more robustly
against measurement noises. The scale of the motion
is estimated based on sparse ground plane matching.

Parameters:

\sigma_\phi=0.1
\sigma_\theta=0.5
\sigma_\psi=0.1

Latex Bibtex:

@inproceedings{Mirabdollah2014GCPR,
author = {Mohammad Hossein Mirabdollah and
B{\"{a}}rbel Mertsching},
title = {On the Second Order Statistics of
Essential Matrix Elements},
booktitle = {Proceeding of 36th German Conference
on Pattern Recognition},
year = {2014},
pages = {547--557}
}

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.