Map2DFusion: Real-time incremental UAV image mosaicing based on monocular SLAM

Shuhui Bu, Yong Zhao, Gang Wan, Zhenbao Liu

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

80 Scopus citations

Abstract

In this paper we present a real-time approach to stitch large-scale aerial images incrementally. A monocular SLAM system is used to estimate camera position and attitude, and meanwhile 3D point cloud map is generated. When GPS information is available, the estimated trajectory is transformed to WGS84 coordinates after time synchronized automatically. Therefore, the output orthoimage retains global coordinates without ground control points. The final image is fused and visualized instantaneously with a proposed adaptive weighted multiband algorithm. To evaluate the effectiveness of the proposed method, we create a publicly available aerial image dataset with sequences of different environments. The experimental results demonstrate that our system is able to achieve high efficiency and quality compared to state-of-the-art methods. In addition, we share the code on the website with detailed introduction and results.

Original languageEnglish
Title of host publicationIROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4564-4571
Number of pages8
ISBN (Electronic)9781509037629
DOIs
StatePublished - 28 Nov 2016
Event2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon, Korea, Republic of
Duration: 9 Oct 201614 Oct 2016

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2016-November
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Country/TerritoryKorea, Republic of
CityDaejeon
Period9/10/1614/10/16

Keywords

  • Adaptive weighted multiband
  • Real-time
  • SLAM
  • Stitching
  • UAVs

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