Photographing long scenes with multi-viewpoint panoramas

• 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

抄録

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.

収録刊行物

• ACM Transactions on Graphics

  ACM Transactions on Graphics 25 (3), 853-861, 2006-07

  Association for Computing Machinery (ACM)

キーワード

• Computer Graphics and Computer-Aided Design

詳細情報

• CRID: 1360294810146343424
• NII論文ID: 30022063459
• DOI: 10.1145/1141911.1141966
• ISSN: 15577368
• ISSN: 07300301
• Web Site: https://dl.acm.org/doi/pdf/10.1145/1141911.1141966
• データソース種別:
  • Crossref
  • CiNii Articles