SCIENCE@home

FrameBreak: Dramatic Image Extrapolation by Guided Shift-Maps

Yinda Zhang,Jianxiong Xiao,James Hays,P. Tan

Published 2013 in 2013 IEEE Conference on Computer Vision and Pattern Recognition

ABSTRACT

We significantly extrapolate the field of view of a photograph by learning from a roughly aligned, wide-angle guide image of the same scene category. Our method can extrapolate typical photos into complete panoramas. The extrapolation problem is formulated in the shift-map image synthesis framework. We analyze the self-similarity of the guide image to generate a set of allowable local transformations and apply them to the input image. Our guided shift-map method reserves to the scene layout of the guide image when extrapolating a photograph. While conventional shift-map methods only support translations, this is not expressive enough to characterize the self-similarity of complex scenes. Therefore we additionally allow image transformations of rotation, scaling and reflection. To handle this increase in complexity, we introduce a hierarchical graph optimization method to choose the optimal transformation at each output pixel. We demonstrate our approach on a variety of indoor, outdoor, natural, and man-made scenes.

PUBLICATION RECORD

  • Publication year

    2013

  • Venue

    2013 IEEE Conference on Computer Vision and Pattern Recognition

  • Publication date

    2013-06-01

  • Fields of study

    Mathematics, Computer Science

  • Identifiers
    DOI 10.1109/CVPR.2013.155
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-29 of 29 references · Page 1 of 1

CITED BY

Showing 1-80 of 80 citing papers · Page 1 of 1