Multi-plane Image Stitching Base on Image Semantic under Large Viewpoint Changes

Dongsheng Wang, Weifeng Wang, Yijin Li, Yi Yang, Meiling Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Traditional image stitching method is under the assumption that the image content is approximately in a same plane, and it will result in severe stitching distortion for images with large viewpoint changes. To solve the problem above, a robust multi-plane image stitching method based on image semantic is proposed in this paper. Assuming that the regions with the same semantic label are in the same plane, the image can be divided into multiple planes with transition borderline by semantic segmentation. Finally, image stitching is completed by mixing multiple image planes with gaussian weights along the borderline, and warping image with perspective and similarity transformation. The experimental results indicate that the proposed method performs more accurately and naturally, and is robust to large viewpoint changes.

Original languageEnglish
Title of host publicationProceedings of the 37th Chinese Control Conference, CCC 2018
EditorsXin Chen, Qianchuan Zhao
PublisherIEEE Computer Society
Pages4357-4362
Number of pages6
ISBN (Electronic)9789881563941
DOIs
Publication statusPublished - 5 Oct 2018
Event37th Chinese Control Conference, CCC 2018 - Wuhan, China
Duration: 25 Jul 201827 Jul 2018

Publication series

NameChinese Control Conference, CCC
Volume2018-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference37th Chinese Control Conference, CCC 2018
Country/TerritoryChina
CityWuhan
Period25/07/1827/07/18

Keywords

  • Image Semantic
  • Image stitching
  • Multi-plane
  • Similarity transformation

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