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conference paper

Dynamic and Scalable Large Scale Image Reconstruction

Strecha, Christoph  
•
Pylvanainen, Timo
•
Fua, Pascal  
2010
Proceedings of 23rd IEEE Conference on Computer Vision and Pattern Recognition
23rd IEEE Conference on Computer Vision and Pattern Recognition

Recent approaches to reconstructing city-sized areas from large image collections usually process them all at once and only produce disconnected descriptions of image subsets, which typically correspond to major landmarks. In contrast, we propose a framework that lets us take advantage of the available meta-data to build a single, consistent description from these potentially disconnected descriptions. Furthermore, this description can be incrementally updated and enriched as new images become avail- able. We demonstrate the power of our approach by building large-scale reconstructions using images of Lausanne and Prague.

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Type
conference paper
DOI
10.1109/CVPR.2010.5540184
Author(s)
Strecha, Christoph  
Pylvanainen, Timo
Fua, Pascal  
Date Issued

2010

Published in
Proceedings of 23rd IEEE Conference on Computer Vision and Pattern Recognition
Start page

406

End page

413

Subjects

bundle adjustment

•

large scale reconstruction

URL

URL

http://cvlab.epfl.ch/~strecha/demos/largescale/
Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CVLAB  
Event nameEvent placeEvent date
23rd IEEE Conference on Computer Vision and Pattern Recognition

San Francisco, U.S.A

June 13-19, 2010

Available on Infoscience
April 12, 2010
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/49316
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