The KITTI Vision Benchmark Suite

Method

[st]Stereo Visual Inertial Pose Estimation Based on Feedforward-Feedback Loops [FLVIS]
https://github.com/HKPolyU-UAV/FLVIS

Submitted on 26 Apr. 2021 13:30 by
Shengyang Chen (MAV Lab, PolyU, HK)

Running time:		0.05 s
Environment:		2 cores @ 2.5 Ghz (C/C++)

Method Description:

Fast visual pose estimation using feedforward-feedback loops.

Parameters:

Two threads (tracking and loop closing). parameters can be found in the "kitti.yaml" file.

Latex Bibtex:

@article{chen2020stereo,
title={Stereo visual inertial pose estimation based on feedforward-feedback loops},
author={Chen, Shengyang and Wen, Chih-Yung and Zou, Yajing and Chen, Wu},
journal={arXiv preprint arXiv:2007.02250},
year={2020}
}

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.