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Authors: Hongchuan Yu and Mohammed Bennamoun

Affiliation: University of Western Australia, Australia

Keyword(s): Range Dataset, Simplification, SVDecomposition, Radial Basis Functions.

Abstract: In this paper, we consider two approaches of simplifying medium- and large-sized range datasets to a compact data point set, based on the Radial Basis Functions (RBF) approximation. The first algorithm uses a Pseudo-Inverse Approach for the case of given basis functions, and the second one uses an SVD-Based Approach for the case of unknown basis functions. The novelty of this paper consists in a novel partition-based SVD algorithm for a symmetric square matrix, which can effectively reduce the dimension of a matrix in a given partition case. Furthermore, this algorithm is combined with a standard clustering algorithm to form our SVD-Based Approach, which can then seek an appropriate partition automatically for dataset simplification. Experimental results indicate that the presented Pseudo-Inverse Approach requires a uniform sampled control point set, and can obtain an optimal least square solution in the given control point set case. While in the unknown control point case, the prese nted SVD-Based Approach can seek an appropriate control point set automatically, and the resulting surface preserves more of the essential details and is prone to less distortions. (More)

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Paper citation in several formats:
Yu, H. and Bennamoun, M. (2006). SIMPLIFIED REPRESENTATION OF LARGE RANGE DATASET. In Proceedings of the First International Conference on Computer Vision Theory and Applications (VISIGRAPP 2006) - Volume 2: VISAPP; ISBN 972-8865-40-6; ISSN 2184-4321, SciTePress, pages 172-179. DOI: 10.5220/0001374201720179

@conference{visapp06,
author={Hongchuan Yu. and Mohammed Bennamoun.},
title={SIMPLIFIED REPRESENTATION OF LARGE RANGE DATASET},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications (VISIGRAPP 2006) - Volume 2: VISAPP},
year={2006},
pages={172-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001374201720179},
isbn={972-8865-40-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the First International Conference on Computer Vision Theory and Applications (VISIGRAPP 2006) - Volume 2: VISAPP
TI - SIMPLIFIED REPRESENTATION OF LARGE RANGE DATASET
SN - 972-8865-40-6
IS - 2184-4321
AU - Yu, H.
AU - Bennamoun, M.
PY - 2006
SP - 172
EP - 179
DO - 10.5220/0001374201720179
PB - SciTePress

- Science and Technology Publications, Lda.
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