Limitations of non model-based recognition schemes

  • Yael Moses
  • Shimon Ullman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)


Approaches to visual object recognition can be divided into model-based and non model-based schemes. In this paper we establish some limitations on non model-based recognition schemes. We show that a consistent non model-based recognition scheme for general objects cannot discriminate between objects. The same result holds even if the recognition function is imperfect, and is allowed to mis-identify each object from a substantial fraction of the viewing directions. We then consider recognition schemes restricted to classes of objects. We define the notion of the discrimination power of a consistent recognition function for a class of objects. The function's discrimination power determines the set of objects that can be discriminated by the recognition function. We show how the properties of a class of objects determine an upper bound on the discrimination power of any consistent recognition function for that class.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Yael Moses
    • 1
  • Shimon Ullman
    • 1
  1. 1.Dept. of Applied Mathematics and Computer ScienceThe Weizmann Institute of ScienceRehovotIsrael

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