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Proceedings Paper

Comparative analysis of hierarchical triangulated irregular networks to represent 3D elevation in terrain databases
Author(s): Mahdi Abdelguerfi; Chris Wynne; Edgar Cooper; Roy V. Ladner; Kevin B. Shaw
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Paper Abstract

Three-dimensional terrain representation plays an important role in a number of terrain database applications. Hierarchical triangulated irregular networks (TINs) provide a variable-resolution terrain representation that is based on a nested triangulation of the terrain. This paper compares and analyzes existing hierarchical triangulation techniques. The comparative analysis takes into account how aesthetically appealing and accurate the resulting terrain representation is. Parameters, such as adjacency, slivers, and streaks, are used to provide a measure on how aesthetically appealing the terrain representation is. Slivers occur when the triangulation produces thin and slivery triangles. Streaks appear when there are too many triangulations done at a given vertex. Simple mathematical expressions are derived for these parameters, thereby providing a fairer and a more easily duplicated comparison. In addition to meeting the adjacency requirement, an aesthetically pleasant hierarchical TINs generation algorithm is expected to reduce both slivers and streaks while maintaining accuracy. A comparative analysis of a number of existing approaches shows that a variant of a method originally proposed by Scarlatos exhibits better overall performance.

Paper Details

Date Published: 5 August 1997
PDF: 11 pages
Proc. SPIE 3072, Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision III, (5 August 1997); doi: 10.1117/12.281040
Show Author Affiliations
Mahdi Abdelguerfi, Univ. of New Orleans (United States)
Chris Wynne, Univ. of New Orleans (United States)
Edgar Cooper, Univ. of New Orleans (United States)
Roy V. Ladner, Univ. of New Orleans (United States)
Kevin B. Shaw, Naval Research Lab. (United States)

Published in SPIE Proceedings Vol. 3072:
Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision III
David M. McKeown; J. Chris McGlone; Olivier Jamet, Editor(s)

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