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Author Seitz, Steven M. ♦ Curless, Brian ♦ Szeliski, Richard ♦ Furukawa, Yasutaka ♦ Snavely, Noah ♦ Simon, Ian ♦ Agarwal, Sameer
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract We present a system that can reconstruct 3D geometry from large, unorganized collections of photographs such as those found by searching for a given city (e.g., Rome) on Internet photo-sharing sites. Our system is built on a set of new, distributed computer vision algorithms for image matching and 3D reconstruction, designed to maximize parallelism at each stage of the pipeline and to scale gracefully with both the size of the problem and the amount of available computation. Our experimental results demonstrate that it is now possible to reconstruct city-scale image collections with more than a hundred thousand images in less than a day.
Description Affiliation: Google Inc. & University of Washington, Washington, Seattle, WA (Seitz, Steven M.) || Microsoft Research, Redmond, WA (Szeliski, Richard) || Microsoft Corporation, Redmond, WA (Simon, Ian) || Cornell University, Ithaca, NY (Snavely, Noah) || Google Inc., Seattle, WA (Agarwal, Sameer; Furukawa, Yasutaka) || University of Washington, Washington, Seattle, WA (Curless, Brian)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 54
Issue Number 10
Page Count 8
Starting Page 105
Ending Page 112

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Source: ACM Digital Library