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Proceedings Paper

Learning procedure for the recognition of 3-D objects from 2-D images
Author(s): Mischa Bart; Johannes Buurman; Robert P. W. Duin
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Paper Abstract

A learning procedure is described for the recognition of 3d industrial objects from 2d images. It is assumed that the objects are solid and have well defmed edges and that viewpoint and lightning are well defined but that there is no information available on the orientation distribution of future objects to be classified. The presented learning procedure covers all orientations by an initial sampling detects gaps and deletes superfluous orientations. An example is presented.

Paper Details

Date Published: 1 February 1991
PDF: 12 pages
Proc. SPIE 1381, Intelligent Robots and Computer Vision IX: Algorithms and Techniques, (1 February 1991); doi: 10.1117/12.25135
Show Author Affiliations
Mischa Bart, Delft Univ. of Technology (Netherlands)
Johannes Buurman, Delft Univ. of Technology (Netherlands)
Robert P. W. Duin, Delft Univ. of Technology (Netherlands)


Published in SPIE Proceedings Vol. 1381:
Intelligent Robots and Computer Vision IX: Algorithms and Techniques
David P. Casasent, Editor(s)

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