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Conference Papers Year : 2015

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

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.
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Dates and versions

hal-01212043 , version 1 (08-10-2015)

Identifiers

  • HAL Id : hal-01212043 , version 1

Cite

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⟩
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