Constructing image panoramas using dual-homography warping

Junhong Gao, Seon Joo Kim, Michael S. Brown

Research output: Chapter in Book/Report/Conference proceedingConference contribution

135 Citations (Scopus)

Abstract

This paper describes a method to construct seamless image mosaics of a panoramic scene containing two predominate planes: a distant back plane and a ground plane that sweeps out from the camera's location. While this type of panorama can be stitched when the camera is carefully rotated about its optical center, such ideal scene capture is hard to perform correctly. Existing techniques use a single homography per image to perform alignment followed by seam cutting or image blending to hide inevitable alignments artifacts. In this paper, we demonstrate how to use two homographies per image to produce a more seamless image. Specifically, our approach blends the homographies in the alignment procedure to perform a nonlinear warping. Once the images are geometrically stitched, they are further processed to blend seams and reduce curvilinear visual artifacts due to the nonlinear warping. As demonstrated in our paper, our procedure is able to produce results for this type of scene where current state-of-the-art techniques fail.

Original languageEnglish
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
PublisherIEEE Computer Society
Pages49-56
Number of pages8
ISBN (Print)9781457703942
DOIs
Publication statusPublished - 2011 Jan 1

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

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All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Gao, J., Kim, S. J., & Brown, M. S. (2011). Constructing image panoramas using dual-homography warping. In 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 (pp. 49-56). [5995433] (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). IEEE Computer Society. https://doi.org/10.1109/CVPR.2011.5995433