Locating objects of varying shape using statistical feature detectors

  • T. F. Cootes
  • C. J. Taylor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1065)


Most deformable models use a local optimisation scheme to locate their targets in images, and require a 'good enough' starting point. This paper describes an approach for generating such starting points automatically given no prior knowledge of the pose of the target(s) in the image. It relies upon choosing a suitable set of features, candidates for which can be found in the image. Hypotheses are formed from sets of candidates, and their plausibility tested using the statistics of their relative positions and orientations. The most plausible are used as the initial position of an Active Shape Model, which can then accurately locate the target object. The approach is demonstrated for two different image interpretation problems.


Face Image Feature Detector Shape Model Deformable Model Combinatorial Explosion 
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 1996

Authors and Affiliations

  • T. F. Cootes
    • 1
  • C. J. Taylor
    • 1
  1. 1.Department of Medical BiophysicsUniversity of ManchesterManchesterUK

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