From Google Street View to 3D City Models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00163723" target="_blank" >RIV/68407700:21230/09:00163723 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
From Google Street View to 3D City Models
Original language description
We present a structure-from-motion (SfM) pipeline for visual 3D modeling of a large city area using 360 deg. field of view Google Street View images. The core of the pipeline combines the state of the art techniques such as SURF feature detection, tentative matching by an approximate nearest neighbour search, relative camera motion estimation by solving 5-pt minimal camera pose problem, and sparse bundle adjustment. The robust and stable camera poses estimated by PROSAC with soft voting and by scale selection using a visual cone test bring high quality initial structure for bundle adjustment. Furthermore, searching for trajectory loops based on co-occurring visual words and closing them by adding new constraints for the bundle adjustment enforce the global consistency of camera poses and 3D structure in the sequence. We present a large-scale reconstruction computed from 4,799 images of the Google Street View Pittsburgh Research Data Set.
Czech name
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Czech description
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Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
OMNIVIS '09: 9th IEEE Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras
ISBN
978-1-4244-4441-0
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
IEEE Computer Society Press
Place of publication
Los Alamitos
Event location
Kyoto
Event date
Oct 4, 2009
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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