Journal
IEEE TRANSACTIONS ON ROBOTICS
Volume 32, Issue 6, Pages 1565-1573Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2016.2609395
Keywords
Background subtraction; dynamic environment; simultaneous localization and mapping (SLAM); visual odometry; visual tracking
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Funding
- National Research Foundation of Korea (NRF) - Korean government (MSIP) [NRF-2014R1A2A1A10051551]
- Technology Innovation Program - Ministry of Trade, Industry and Energy (MOTIE, Korea) [10045252]
- Korea Evaluation Institute of Industrial Technology (KEIT) [10045252] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [2014R1A2A1A10051551] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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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.
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