Recovering Euclidean structure from principal-axes paralleled conics: Applications to camera calibration

Zijian Zhao, Ying Weng

Research output: Journal PublicationArticlepeer-review

5 Citations (Scopus)

Abstract

We focus on recovering the 2D Euclidean structure further for camera calibration from the projections of N parallel similar conics in this paper. This work demonstrates that the conic dual to the absolute points (CDAP) is the general form of the conic dual to the circular points, so it encodes the 2D Euclidean structure. However, the geometric size of the conic should be known if we utilize the CDAP. Under some special conditions (concentric conics), we proposed the rank-1 and rank-2 constraints. Our work relaxes the problem conditions and gives a more general framework than before. Experiments with simulated and real data are carried out to show the validity of the proposed algorithm.

Original languageEnglish
Pages (from-to)1186-1193
Number of pages8
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume31
Issue number6
DOIs
Publication statusPublished - 1 Jun 2014
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition

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