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Proceedings Paper

Object recognition using eigenvectors
Author(s): Ovidiu Ghita; Paul F. Whelan
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Paper Abstract

A method for object recognition and pose estimation for robotic bin picking is presented. The approach discussed is a variant on current approaches to eigenimage analysis. Compared to traditional approaches which use object geometry only (shape invariants), the implementation described uses the eigenspace determined by processing the eigenvalues and eigenvectors of the image set. The image set is obtained by varying pose while maintaining a constant level of illumination in space, and the eigenspace is computed for each object of interest. For an unknown input image, the recognition algorithm projects this image to each eigenspace and the object is recognized using space partitioning methods which determine the object and the position in space. Several experimental results have been obtained to demonstrate the robustness of this method when applied to the robotic bin picking task.

Paper Details

Date Published: 26 September 1997
PDF: 7 pages
Proc. SPIE 3208, Intelligent Robots and Computer Vision XVI: Algorithms, Techniques, Active Vision, and Materials Handling, (26 September 1997); doi: 10.1117/12.290331
Show Author Affiliations
Ovidiu Ghita, Dublin City Univ. (Ireland)
Paul F. Whelan, Dublin City Univ. (Ireland)


Published in SPIE Proceedings Vol. 3208:
Intelligent Robots and Computer Vision XVI: Algorithms, Techniques, Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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