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Proceedings Paper

Three-dimensional range image segmentation and fitting by quadratic surfaces
Author(s): Xinming Yu; Tien D. Bui; Adam Krzyzak
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Paper Abstract

This paper presents a robust segmentation and fitting technique. The method randomly samples appropriate range image points and fits them into selected primitive type. From K samples we measure residual consensus to choose one set of sample points which determines an equation to have the best fit for a homogeneous patch in the current processing region. A method with compressed histogram is used to measure and compare residuals on various noise levels. The method segments range image into quadratic surfaces, and works very well even in smoothly connected regions.

Paper Details

Date Published: 30 April 1992
PDF: 10 pages
Proc. SPIE 1611, Sensor Fusion IV: Control Paradigms and Data Structures, (30 April 1992); doi: 10.1117/12.57954
Show Author Affiliations
Xinming Yu, Concordia Univ. (Canada)
Tien D. Bui, Concordia Univ. (Canada)
Adam Krzyzak, Concordia Univ. (Canada)

Published in SPIE Proceedings Vol. 1611:
Sensor Fusion IV: Control Paradigms and Data Structures
Paul S. Schenker, Editor(s)

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