Robust plane-based calibration of multiple non-overlapping cameras

Chen Zhu, Zihan Zhou, Ziran Xing, Yanbing Dong, Yi Ma, Jingyi Yu

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

8 Scopus citations

Abstract

The availability of commodity multi-camera systems such as Google Jump, Jaunt, and Lytro Immerge have brought new demand for reliable and efficient extrinsic camera calibration. State-of-the-art solutions generally require that adjacent, if not all, cameras observe a common area or employ known scene structures. In this paper, we present a novel multi-camera calibration technique that eliminates such requirements. Our approach extends the single-pair hand-eye calibration used in robotics to multi-camera systems. Specifically, we make use of (possibly unknown) planar structures in the scene and combine plane-based structure from motion, camera pose estimation, and task-specific bundle adjustment for extrinsic calibration. Experiments on several multi-camera setups demonstrate that our scheme is highly accurate, robust, and efficient.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 4th International Conference on 3D Vision, 3DV 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages658-666
Number of pages9
ISBN (Electronic)9781509054077
DOIs
StatePublished - Dec 15 2016
Event4th International Conference on 3D Vision, 3DV 2016 - Stanford, United States
Duration: Oct 25 2016Oct 28 2016

Publication series

NameProceedings - 2016 4th International Conference on 3D Vision, 3DV 2016

Conference

Conference4th International Conference on 3D Vision, 3DV 2016
CountryUnited States
CityStanford
Period10/25/1610/28/16

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing

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