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Proceedings Paper

Automatic construction of a relational model for recognition of a 3-D object
Author(s): Shujun Zhang; Geoffrey D. Sullivan; K. D. Baker
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Paper Abstract

This paper presents a view-independent relational model (VIRM) for use in a vision system designed for recognizing known 3D objects from single monochromatic images within unknown environments. The aim if to establish a model of an object suitable for its recognition automatically without invoking pose information. To generate the VIRM, the system projects a wireframe model of the object from a number of different viewpoints, and performs a statistical inference to select relatively view-independent relationships among component parts of the object. These relations are stored as a relational model of the object represented as a hypergraph associated with procedural constraints. Three-dimensional component parts (model features) of the object, which can be associated with extended image features defined by simple 2D geometrical attributes, are used as nodes of the hypergraph. Co- visibility of model features is represented by arcs of the hypergraph. Other pairwise view- independent relations are used as procedural constraints associated with arcs of the hypergraph.

Paper Details

Date Published: 1 February 1992
PDF: 12 pages
Proc. SPIE 1609, Model-Based Vision Development and Tools, (1 February 1992); doi: 10.1117/12.57129
Show Author Affiliations
Shujun Zhang, Univ. of Reading (United Kingdom)
Geoffrey D. Sullivan, Univ. of Reading (United Kingdom)
K. D. Baker, Univ. of Reading (United Kingdom)

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

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