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Shape, Contour and Grouping in Computer Vision pp 31–57Cite as

Shape Models and Object Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1681))

Abstract

This paper discusses some problems that should be addressed by future object recognition systems.

In particular, there are things that we know how to do today, for example:

  1. 1.

    Computing the pose of a free-form three-dimensional object from its outline (e.g. [106]).

  2. 2.

    Identifying a polyhedral object from point and line features found in an image (e.g., [46, 89]).

  3. 3.

    Recognizing a solid of revolution from its outline (e.g., [59]).

  4. 4.

    Identifying a face with a fixed pose in a photograph (e.g., [10, 111]).

This work was partially supported by the National Science Foundation under grant IRI-9634312 and by the Beckman Institute at the University of Illinois at Urbana- Champaign. M. Cepeda is now with Qualcomm, Inc. and S. Sullivan is now with Industrial Light and Magic.

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  1. Dept. of Computer Science and Beckman Institute, University of Illinois, Urbana, IL, 61801, USA

    Jean Ponce, Martha Cepeda, Sung-il Pae & Steve Sullivan

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Ponce, J., Cepeda, M., Pae, Si., Sullivan, S. (1999). Shape Models and Object Recognition. In: Shape, Contour and Grouping in Computer Vision. Lecture Notes in Computer Science, vol 1681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46805-6_4

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