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Photographing long scenes with multi-viewpoint panoramas
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Source ACM Transactions on Graphics (TOG) archive
Volume 25 ,  Issue 3  (July 2006) table of contents
Proceedings of ACM SIGGRAPH 2006
SESSION: Image collections table of contents
Pages: 853 - 861  
Year of Publication: 2006
ISSN:0730-0301
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Authors
Aseem Agarwala  University of Washington
Maneesh Agrawala  University of California, Berkeley
Michael Cohen  Microsoft Research
David Salesin  University of Washington and Adobe Systems
Richard Szeliski  Microsoft Research
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present a system for producing multi-viewpoint panoramas of long, roughly planar scenes, such as the facades of buildings along a city street, from a relatively sparse set of photographs captured with a handheld still camera that is moved along the scene. Our work is a significant departure from previous methods for creating multi-viewpoint panoramas, which composite thin vertical strips from a video sequence captured by a translating video camera, in that the resulting panoramas are composed of relatively large regions of ordinary perspective. In our system, the only user input required beyond capturing the photographs themselves is to identify the dominant plane of the photographed scene; our system then computes a panorama automatically using Markov Random Field optimization. Users may exert additional control over the appearance of the result by drawing rough strokes that indicate various high-level goals. We demonstrate the results of our system on several scenes, including urban streets, a river bank, and a grocery store aisle.


REFERENCES

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CITED BY  17

Collaborative Colleagues:
Aseem Agarwala: colleagues
Maneesh Agrawala: colleagues
Michael Cohen: colleagues
David Salesin: colleagues
Richard Szeliski: colleagues