Tracking of rotating objects

  • Gabriele Peters
  • Christian Eckes
  • Christoph von der Malsburg
Poster Papers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1451)


A representation of a three-dimensional object is autonomously learned from a sequence of the rotating object. The representation consists of single views in form of graphs and is achieved by performing a segmentation-based tracking of the object. First we apply a segmentation algorithm which is based on gray level values. This provides the location o£ the object in the images and a rough shape of it. Then we position landmarks on the object in the first frame of the sequence. These landmarks are tracked throughout the sequence on the basis of Gabor wavelet responses and guided by the segmentation result. During rotation landmarks are lost and new landmarks are added when object parts vanish or come into sight, respectively.


  1. [1]
    C. Eckes; J. C. Vorbrüggen; Combining Data-Driven and Model-Based Cues for Segmentation of Video Sequences; Proceedings WCNN96, INNS Press & Lawrence Erlbaum Ass.; San Diego; CA; USA; 16-18 September; pp. 868–875; 1996.Google Scholar
  2. [2]
    J. C. Vorbrüggen; Zwei Modelle zur datengetriebenen Segmentierung visueller Daten; PhD-thesis; Ruhr-Universität Bochum; 1994.Google Scholar
  3. [3]
    M. Wertheimer, Untersuchungen zur Lehre von der Gestalt. II, Psychol Forschung, vol 4; pp. 301–350; 1923.CrossRefGoogle Scholar
  4. [4]
    N. Metropolis; A. Rosenbluth; M. Rosenbluth; A. Teller; E. Teller; Introduction of the Metropolis Algorithm for Molecular-Dynamics Simulation; J. Chem. Phys; vol. 21; p. 1987; 1953.CrossRefGoogle Scholar
  5. [5]
    T. Maurer, C. von der Malsburg; Tracking and Learning Graphs and Pose on Image Sequences of Faces; Proc.,2nd Int. Conf. on Automatic Face-and Gesture-Recognition; Killington, Vermont; USA; IEEE Camp. Soc. Press. Los Alamitos, California; pp. 176–181, 1996.Google Scholar
  6. [6]
    D. J. Fleet; A. D. Jepson; Computation of Component Image Velocity from Local Phase Information; Int. Journal of Computer Vision, vol. 5(1), p. 77; 1990.CrossRefGoogle Scholar
  7. [7]
    W. M. Theimer; H. A.Mallot, Phase-Based Binocular Vergence Control and Depth Reconstruction using Active Vision; CVGIP. Image Understanding; vol. 60(3); p. 343. 1994.CrossRefGoogle Scholar
  8. [8]
    J. J. Koenderink; A. J. van Doorn; The Singularities of the Visual Mapping: Biological Cybernetics; vol.24, pp. 51–59, 1976.CrossRefPubMedGoogle Scholar
  9. [9]
    M. F. Roy; T. van Effelterre; Aspect Graphs of Algebraic Surfaces; Proceedings of the 1993 International Symposium on Symbolic and Algebraic Computation; pp. 135–143,1993.xGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Gabriele Peters
    • 1
  • Christian Eckes
    • 1
  • Christoph von der Malsburg
    • 1
  1. 1.Institut für NeuroinformatikRuhr-Universität Bochum, SystembiophysikBochumGermany

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