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Proceedings Paper

A Parallel Environment For Structural Analysis Of Range Imagery
Author(s): A. Perez; M. A. Abidi; R. C. Gonzalez
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Paper Abstract

Rigid objects can be modeled by quadric or planar polyhedra. This representation allows low-level data driven algorithms to determine the identity and pose of an object. Before an object can be matched with an internal model, however, its image must be first segmented into basic components, such as smooth patches. This paper describes a low-level parallel range data analysis system that uses input range data to characterize the underlying scene in terms of the visible surfaces, using simpl0e, invariant features to generate a view independent description of the scene. The central components of the system are a parallel segmenter and a parallel surface fitter. The segmentation algorithms are based on the estimation of surface curvatures. Surface fitting allows for pose estimation and recognition of objects in range scenes. Mathematically, surface fitting can be formulated as an overdetermined linear system which can be solved in the least-square sense. Because of numerical stability and ease of implementation, the QR-factorization using the Givens transformation is suited for the parallel solution of overdetermined systems. We discuss the implementation of the range analysis system on a distributed-memory hypercube parallel computer.

Paper Details

Date Published: 22 August 1988
PDF: 8 pages
Proc. SPIE 0938, Digital and Optical Shape Representation and Pattern Recognition, (22 August 1988); doi: 10.1117/12.976580
Show Author Affiliations
A. Perez, University of Tennessee (United States)
M. A. Abidi, University of Tennessee (United States)
R. C. Gonzalez, University of Tennessee and Perceptics Corporation (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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