Data-driven MCMC sampling for vision-based 6D SLAM

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An efficient sampling technique for estimating camera motion is presented. For this purpose, Markov chain Monte Carlo (MCMC) sampling is incorporated into the data-driven proposal distribution in order to improve the SLAM performance. Experimental results using both synthetic and real datasets demonstrate the efficiency of the proposed method.
Publisher
INST ENGINEERING TECHNOLOGY-IET
Issue Date
2012-06
Language
English
Article Type
Article
Citation

ELECTRONICS LETTERS, v.48, no.12, pp.687 - 689

ISSN
0013-5194
DOI
10.1049/el.2012.0897
URI
http://hdl.handle.net/10203/104540
Appears in Collection
EE-Journal Papers(저널논문)
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