Robust Pose Estimation from a Planar Target

Gerald Schweighofer, Axel Pinz

    Research output: Contribution to journalArticlepeer-review


    In theory, the pose of a calibrated camera can be uniquely determined from a minimum of four coplanar but noncollinear points. In practice, there are many
    applications of camera pose tracking from planar targets and there is also a number of recent pose estimation algorithms which perform this task in real-time, but all of these algorithms suffer from pose ambiguities. This paper investigates the pose ambiguity for planar targets viewed by a perspective camera. We show that pose ambiguities—two distinct local minima of the according error function—exist even for cases with wide angle lenses and close range targets. We give a comprehensive interpretation of the two minima and derive an analytical solution that locates the second minimum. Based on this solution, we develop a new algorithm for unique and robust pose estimation from a planar target. In the experimental evaluation, this algorithm outperforms four state-of-the-art pose estimation algorithms.
    Original languageEnglish
    Pages (from-to)2024-2030
    JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
    Issue number12
    Publication statusPublished - 2006


    • Camera pose ambiguity
    • pose tracking

    Treatment code (Nähere Zuordnung)

    • Basic - Fundamental (Grundlagenforschung)
    • Theoretical


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