Robust factorization

Henrik Aanæs, Rune Fisker, Kalle Åström, Jens Michael Carstensen

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    Abstract

    Factorization algorithms for recovering structure and motion from an image stream have many advantages, but they usually require a set of well-tracked features. Such a set is in generally not available in practical applications. There is thus a need for making factorization algorithms deal effectively with errors in the tracked features. We propose a new and computationally efficient algorithm for applying an arbitrary error function in the factorization scheme. This algorithm enables the use of robust statistical techniques and arbitrary noise models for the individual features. These techniques and models enable the factorization scheme to deal effectively with mismatched features, missing features, and noise on the individual features. The proposed approach further includes a new method for Euclidean reconstruction that significantly improves convergence of the factorization algorithms. The proposed algorithm has been implemented as a modification of the Christy-Horaud factorization scheme, which yields a perspective reconstruction. Based on this implementation, a considerable increase in error tolerance is demonstrated on real and synthetic data. The proposed scheme can, however, be applied to most other factorization algorithms.
    Original languageEnglish
    JournalI E E E Transactions on Pattern Analysis and Machine Intelligence
    Volume24
    Issue number9
    Pages (from-to)1215-1225
    ISSN0162-8828
    DOIs
    Publication statusPublished - 2002

    Bibliographical note

    Copyright: 2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

    Cite this

    Aanæs, H., Fisker, R., Åström, K., & Carstensen, J. M. (2002). Robust factorization. I E E E Transactions on Pattern Analysis and Machine Intelligence, 24(9), 1215-1225. https://doi.org/10.1109/TPAMI.2002.1033213