Skip to Main content Skip to Navigation
New interface
Conference papers

Robust Dense Visual Odometry For RGB-D Cameras In A Dynamic Environment

Abdallah Dib 1, 2 François Charpillet 2, 1 
Abstract : —The aim of our work is to estimate the camera motion from RGB-D images in a dynamic scene. Most of the existing methods have a poor localization performance in such environments, which makes them inapplicable in real world conditions. In this paper, we propose a new dense visual odometry method that uses RANSAC to cope with dynamic scenes. We show the efficiency and robustness of the proposed method on a large set of experiments in challenging situations and from publicly available benchmark dataset. Additionally, we compare our approach to another state-of-art method based on M-estimator that is used to deal with dynamic scenes. Our method gives similar results on benchmark sequences and better results on our own dataset.
Complete list of metadata

Cited literature [26 references]  Display  Hide  Download
Contributor : dib abdallah Connect in order to contact the contributor
Submitted on : Thursday, October 8, 2015 - 9:54:13 AM
Last modification on : Monday, July 25, 2022 - 3:44:44 AM
Long-term archiving on: : Saturday, January 9, 2016 - 10:11:42 AM


Files produced by the author(s)


  • HAL Id : hal-01212043, version 1


Abdallah Dib, François Charpillet. Robust Dense Visual Odometry For RGB-D Cameras In A Dynamic Environment. International Conference on Advanced Robotics ICAR 2015, Jul 2015, Istanbul, Turkey. ⟨hal-01212043⟩



Record views


Files downloads