The KITTI Vision Benchmark Suite

Method

[st]Robust and Accurate Deterministic Visual Odometry [RADVO]

Submitted on 25 Aug. 2020 10:02 by
Pierre Bénet (SBG systems)

Running time:		0.07 s
Environment:		1 core @ 3.0 Ghz (C/C++)

Method Description:

-Front-end based on Stereoscan descriptor and matching.
-Rotation estimation based on epipolar constraint parametrization.
-Translation estimation using meansquare and loss function.
-Accurate uncertainty propagation using EKF.
-keyframing
-rotation merging

Parameters:

30% outliers

Latex Bibtex:

@inproceedings{Benet_Guinamard_2020,
title={Robust and Accurate Deterministic Visual Odometry},
url={http://dx.doi.org/10.33012/2020.17586},
DOI={10.33012/2020.17586},
booktitle={Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020)}, publisher={Institute of Navigation}, author={Bénet, Pierre and Guinamard, Alexis}, year={2020}, month={Oct} }

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.