Effective Background Model-Based RGB-D Dense Visual Odometry in a Dynamic Environment

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This paper proposes a robust background model-based dense-visual-odometry (BaMVO) algorithm that uses an RGB-D sensor in a dynamic environment. The proposed algorithm estimates the background model represented by the nonparametric model from depth scenes and then estimates the ego-motion of the sensor using the energy-based dense-visual-odometry approach based on the estimated background model in order to consider moving objects. Experimental results demonstrate that the ego-motion is robustly obtained by BaMVO in a dynamic environment.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2016-12
Language
English
Article Type
Article
Keywords

MARS EXPLORATION ROVERS; VEHICLES

Citation

IEEE TRANSACTIONS ON ROBOTICS, v.32, no.6, pp.1565 - 1573

ISSN
1552-3098
DOI
10.1109/TRO.2016.2609395
URI
http://hdl.handle.net/10203/220175
Appears in Collection
EE-Journal Papers(저널논문)
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