Photographing long scenes with multi-viewpoint panoramas

被引:115
作者
Agarwala, Aseem [1 ]
Agrawala, Maneesh
Cohen, Michael
Salesin, David
Szeliski, Richard
机构
[1] Univ Washington, Seattle, WA 98195 USA
[2] Univ Calif Berkeley, Berkeley, CA 94720 USA
[3] Microsoft Corp, Res, Redmond, WA 98052 USA
[4] Adobe Syst, San Jose, CA 95110 USA
来源
ACM TRANSACTIONS ON GRAPHICS | 2006年 / 25卷 / 03期
关键词
D O I
10.1145/1141911.1141966
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页码:853 / 861
页数:9
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