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On the recognition of parameterized 2D objects

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Abstract

Determining the identity and pose of oceluded objects from noisy data is a critical step in interacting intelligently with an unstructured environment. Previous work has shown that local measurements of position and surface orientation may be used in a constrained search process to solve this problem, for the case of rigid objects, either two-dimensional or three-dimensional. This paper considers the more general problem of recognizing and locating objects that can vary in parameterized ways. We consider two-dimensional objects with rotational, translational, or scaling degrees of freedom, and two-dimensional objects that undergo stretching transformations. We show that the constrained search method can be extended to handle the recognition and localization of such generalized classes of object families.

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Authors and Affiliations

  1. MIT Artificial Intelligence Laboratory, 545 Technology Square, 02139, Cambridge, MA

    W. Eric L. Grimson

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  1. W. Eric L. Grimson
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Additional information

This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by an Office of Naval Research University Research Initiative grant under contract N00014-86-K-0180, in part by the Advanced Research Projects Agency of the Department of Defense under Army contract number DACA76-85-C-0010, and in part by DARPA under. Office of Naval Research contract N00014-85-K-0124. A preliminary version of this work appeared in the proceedings of the First International Conference on Computer Vision, London, England, 1987.

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Grimson, W.E.L. On the recognition of parameterized 2D objects. Int J Comput Vision 2, 353–372 (1989). https://doi.org/10.1007/BF00133555

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