DocumentCode :
2261953
Title :
Scalable multi-view stereo
Author :
Jancosek, Michal ; Shekhovtsov, Alexander ; Pajdla, Tomas
Author_Institution :
Dept. of Cybern., Czech Tech. Univ. in Prague, Prague, Czech Republic
fYear :
2009
fDate :
Sept. 27 2009-Oct. 4 2009
Firstpage :
1526
Lastpage :
1533
Abstract :
This paper presents a scalable multi-view stereo reconstruction method which can deal with a large number of large unorganized images in affordable time and effort. The computational effort of our technique is a linear function of the surface area of the observed scene which is conveniently discretized to represent sufficient but not excessive detail. Our technique works as a filter on a limited number of images at a time and can thus process arbitrarily large data sets using limited memory. By building reconstructions gradually, we avoid unnecessary processing of data which bring little improvement. In experiments with Middlebury and Strecha´s databases, we demonstrate that we achieve results comparable to the state of the art with considerably smaller effort than used by previous methods. We present a large scale experiments in which we processed 294 unorganized images of an outdoor scene and reconstruct its 3D model and 1000 images from the Google Street View Pittsburgh Experimental Data Set.
Keywords :
filtering theory; image reconstruction; stereo image processing; 3D model; Google Street View Pittsburgh experimental data set; Middlebury database; Strecha databases; data processing; filter; linear function technique; scalable multiview stereo reconstruction method; Cameras; Conferences; Cybernetics; Image databases; Image reconstruction; Large-scale systems; Layout; Pixel; Stereo image processing; Stereo vision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-4442-7
Electronic_ISBN :
978-1-4244-4441-0
Type :
conf
DOI :
10.1109/ICCVW.2009.5457432
Filename :
5457432
Link To Document :
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