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Proceedings Paper

Object recognition and integration using surface signatures and neural networks
Author(s): Ahmed M. Elbialy
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Paper Abstract

In this paper we present a new technique for 3D free-form object recognition using neural networks, and a novel surface representation scheme. This new scheme encodes the 3D surface information into a 2D image. This 2D image corresponds to a certain point on the surface. This image is invariant to both position and orientation and is unique for this point. Therefore, we called this image Surface Point Signature (SPS). Using specially designed neural networks, the SPS images are used in the matching and recognition of 3D objects in a 3D-scanned scene.

Paper Details

Date Published: 26 August 1999
PDF: 10 pages
Proc. SPIE 3839, Sensor Fusion and Decentralized Control in Robotic Systems II, (26 August 1999); doi: 10.1117/12.360347
Show Author Affiliations
Ahmed M. Elbialy, Cairo Univ. (Egypt)


Published in SPIE Proceedings Vol. 3839:
Sensor Fusion and Decentralized Control in Robotic Systems II
Gerard T. McKee; Paul S. Schenker, Editor(s)

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