Share Email Print

Proceedings Paper

Model-based 3-D object recognition using scalar transform descriptors
Author(s): Kenneth Dawson; David St. G. Vernon
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Three dimensional object recognition is an essential capability for any advanced machine vision system. We present a new technique for the recognition of 3-D objects on the basis of comparisons between 3-D models. Secondary representations of the models, which may be considered as complex scalar transform descriptors, are employed. The use of these representations overcomes the common dependency of matching individual model primitives (such as edges or surfaces). The secondary representations used are one-dimensional histograms of components of the visible orientations, depth maps and needle diagrams. Matching is achieved using template matching and normalized correlation techniques between the secondary representations. We demonstrate the power of this new technique with several examples of object recognition of models derived from actively sensed range data.

Paper Details

Date Published: 1 February 1992
PDF: 12 pages
Proc. SPIE 1609, Model-Based Vision Development and Tools, (1 February 1992); doi: 10.1117/12.57132
Show Author Affiliations
Kenneth Dawson, Univ. of Dublin/Trinity College (Ireland)
David St. G. Vernon, Univ. of Dublin/Trinity College (Ireland)

Published in SPIE Proceedings Vol. 1609:
Model-Based Vision Development and Tools
Rodney M. Larson; Hatem N. Nasr, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?