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Appearance-based 3D object recognition

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Object Representation in Computer Vision (ORCV 1994)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 994))

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Abstract

General, three-dimensional object recognition is still an unsolved problem. A major handicap in many systems is the use of standard point and straight-line-segment features for recognition. We believe that general object recognition can only be accomplished by utilizing the appropriate sensors for each object class and the appropriate features that can be reliably extracted using those sensors. We also believe that the analysis of complex scenes will require an active system. In this paper we define a new representation called an appearanced-based model and discuss its use for hypothesize-and-test object recognition in an active environment.

This research was supported by the National Science Foundation under grant number IRI-9023977, by the Boeing Commercial Airplane Group, and by the Washington Technology Center.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, FT-10, University of Washington, 98195, Seattle, WA, USA

    Linda G. Shapiro & Mauro S. Costa

  2. Department of Computer Science & Engineering, FR-35, University of Washington, 98195, Seattle, WA, USA

    Linda G. Shapiro

Authors
  1. Linda G. Shapiro
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  2. Mauro S. Costa
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Editor information

Martial Hebert Jean Ponce Terry Boult Ari Gross

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© 1995 Springer-Verlag Berlin Heidelberg

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Shapiro, L.G., Costa, M.S. (1995). Appearance-based 3D object recognition. In: Hebert, M., Ponce, J., Boult, T., Gross, A. (eds) Object Representation in Computer Vision. ORCV 1994. Lecture Notes in Computer Science, vol 994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60477-4_3

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  • DOI: https://doi.org/10.1007/3-540-60477-4_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60477-8

  • Online ISBN: 978-3-540-47526-2

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