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Proceedings Paper

A Primitive-Based 3D Object Recognition System
Author(s): Atam P. Dhawan
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Paper Abstract

A knowledge-based 3D object recognition system has been developed. The system uses the hierarchical structural, geometrical and relational knowledge in matching the 3D object models to the image data through pre-defined primitives. The primitives, we have selected, to begin with, are 3D boxes, cylinders, and spheres. These primitives as viewed from different angles covering complete 3D rotation range are stored in a "Primitive-Viewing Knowledge-Base" in form of hierarchical structural and relational graphs. The knowledge-based system then hypothesizes about the viewing angle and decomposes the segmented image data into valid primitives. A rough 3D structural and relational description is made on the basis of recognized 3D primitives. This description is now used in the detailed high-level frame-based structural and relational matching. The system has several expert and knowledge-based systems working in both stand-alone and cooperative modes to provide multi-level processing. This multi-level processing utilizes both bottom-up (data-driven) and top-down (model-driven) approaches in order to acquire sufficient knowledge to accept or reject any hypothesis for matching or recognizing the objects in the given image.

Paper Details

Date Published: 22 August 1988
PDF: 9 pages
Proc. SPIE 0938, Digital and Optical Shape Representation and Pattern Recognition, (22 August 1988); doi: 10.1117/12.976619
Show Author Affiliations
Atam P. Dhawan, University of Houston (United States)

Published in SPIE Proceedings Vol. 0938:
Digital and Optical Shape Representation and Pattern Recognition
Richard D. Juday, Editor(s)

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