SEAGULL: Seam-guided local alignment for parallax-tolerant image stitching

Kaimo Lin, Nianjuan Jiang, Loong Fah Cheong, Minh Do, Jiangbo Lu

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


Image stitching with large parallax is a challenging problem. Global alignment usually introduces noticeable artifacts. A common strategy is to perform partial alignment to facilitate the search for a good seam for stitching. Different from existing approaches where the seam estimation process is performed sequentially after alignment, we explicitly use the estimated seam to guide the process of optimizing local alignment so that the seam quality gets improved over each iteration. Furthermore, a novel structure-preserving warping method is introduced to preserve salient curve and line structures during the warping. These measures substantially improve the effectiveness of our method in dealing with a wide range of challenging images with large parallax.

Original languageEnglish (US)
Title of host publicationComputer Vision - 14th European Conference, ECCV 2016, Proceedings
EditorsBastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
Number of pages16
ISBN (Print)9783319464862
StatePublished - 2016
Externally publishedYes
Event14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands
Duration: Oct 11 2016Oct 14 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9907 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other14th European Conference on Computer Vision, ECCV 2016

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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