A fuzzy inference approach to template-based visual tracking View Full Text


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Article Info

DATE

2011-01-06

AUTHORS

Juan-Pablo Ramirez-Paredes, Raul E. Sanchez-Yanez, Victor Ayala-Ramirez

ABSTRACT

The tracking of visual features using appearance models is a well studied but still open area of computer vision. In the absence of knowledge about the structural constraints of the tracked object, the validity of the model can be compromised if only appearance information is used. We propose a fuzzy inference scheme that can be used to selectively update a given template-based model in tracking tasks. This allows us to track moving objects under translation, rotation, and scale changes with minimal feature drift. Moreover, no rigidity constraint needs to be enforced on the moving target. Some experiments have been performed using several targets, and the results are very close to the ground truth paths. The computational cost of our approach is low enough to allow its application in real-time tracking using modest hardware requirements. More... »

PAGES

427-439

References to SciGraph publications

  • 2001-11. Saliency, Scale and Image Description in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2004-05. Robust Real-Time Face Detection in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2004-10. Scale & Affine Invariant Interest Point Detectors in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2009-03-20. Statistical M-Estimation and Consistency in Large Deformable Models for Image Warping in JOURNAL OF MATHEMATICAL IMAGING AND VISION
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    http://scigraph.springernature.com/pub.10.1007/s00138-010-0314-8

    DOI

    http://dx.doi.org/10.1007/s00138-010-0314-8

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