Shape Tracking Using Centroid-Based Methods

  • Arnaldo J. Abrantes
  • Jorge S. Marques
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2134)


Algorithms for tracking generic 2D object boundaries in a video sequence should not make strong assumptions about the shapes to be tracked. When only a weak prior is at hand, the tracker performance becomes heavily dependent on its ability to detect image features; to classify them as informative (i.e., belonging to the object boundary) or as outliers; and to match the informative features with corresponding model points. Unlike simpler approaches often adopted in tracking problems, this work looks at feature classification and matching as two unsu-pervised learning problems. Consequently, object tracking is converted into a problem of dynamic clustering of data, which is solved using competitive learning algorithms. It is shown that competitive learning is a key technique for obtaining accurate local motion estimates (avoiding aperture problems) and for discarding the outliers. In fact, the competitive learning approach shows several benefits: (i) a gradual propagation of shape information across the model; (ii) the use of shape and noise models competing for explaining the data; and (iii) the possibility of adopting high dimensional feature spaces containing relevant information extracted from the image. This work extends the unified framework proposed by the authors in [1].


Object Boundary Model Point Model Sample Edge Point Active Contour Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Arnaldo J. Abrantes
    • 1
  • Jorge S. Marques
    • 2
  1. 1.Department of Electrical and Computer EngineeringInstituto Superior de Engenharia de LisboaLisbonPortugal
  2. 2.Institute for Systems and RoboticsInstituto Superior TécnicoLisbonPortugal

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