Presentation 2014-03-06
Geomorphological Feature Extraction Based on Geometric Context and Self-Localization
Yoshihiro MINAMIDA, Kota AOKI, Hiroshi NAGAHASHI,
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Abstract(in English) Self-localization from camera images is an important technology for mobile robot's sensing. Detecting landmark of which position is known and 3D structure estimation from detected lines are utilized at prior works. These method, however, have constraints on photographic condition or structure of subjects. Our method estimates geomorphological features from an image without any constraint on subjects. In our method, we utilize Geometric Context that calculates the confidence factor of geometric classes from image features. We estimate a point on a map by matching geomorphological features calculated both from images and the map. The experimental result shows that our method could estimate a point to within 10 meters of the ground truth location.
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Keyword(in English) Self-Localization / Geometric Context / Geomorphological feature / Monocular Image
Paper # IMQ2013-42,IE2013-151,MVE2013-80
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Committee MVE
Conference Date 2014/2/27(1days)
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Registration To Media Experience and Virtual Environment (MVE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Geomorphological Feature Extraction Based on Geometric Context and Self-Localization
Sub Title (in English)
Keyword(1) Self-Localization
Keyword(2) Geometric Context
Keyword(3) Geomorphological feature
Keyword(4) Monocular Image
1st Author's Name Yoshihiro MINAMIDA
1st Author's Affiliation Graduate school of Science and Engineering, Tokyo Institute of Technology()
2nd Author's Name Kota AOKI
2nd Author's Affiliation Imaging Science and Engineering Laboratory, Tokyo Institute of Technology
3rd Author's Name Hiroshi NAGAHASHI
3rd Author's Affiliation Imaging Science and Engineering Laboratory, Tokyo Institute of Technology
Date 2014-03-06
Paper # IMQ2013-42,IE2013-151,MVE2013-80
Volume (vol) vol.113
Number (no) 470
Page pp.pp.-
#Pages 4
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