Recovering Euclidean Structure from Principal-axes paralleled conics: Applications to camera calibration

Y. Weng, Z.W. Zhao

    Research output: Contribution to journalArticlepeer-review

    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
    JournalJournal of the Optical Society of America. A, Optics, image science and vision
    Volume31
    Issue number6
    DOIs
    Publication statusPublished - 1 Jun 2014

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