Robust Range Image Registration Using Genetic Algorithms and the Surface Interpenetration Measure

Robust Range Image Registration Using Genetic Algorithms and the Surface Interpenetration Measure

by Kim L Boyer, Luciano Silva, Olga R P Bellon
     
 

ISBN-10: 9812561080

ISBN-13: 9789812561084

Pub. Date: 12/28/2004

Publisher: World Scientific Publishing Company, Incorporated

This book addresses the range image registration problem for automatic 3D model construction. The focus is on obtaining highly precise alignments between different view pairs of the same object to avoid 3D model distortions; in contrast to most prior work, the view pairs may exhibit relatively little overlap and need not be prealigned. To this end, a novel effective

Overview

This book addresses the range image registration problem for automatic 3D model construction. The focus is on obtaining highly precise alignments between different view pairs of the same object to avoid 3D model distortions; in contrast to most prior work, the view pairs may exhibit relatively little overlap and need not be prealigned. To this end, a novel effective evaluation metric for registration, the Surface Interpenetration Measure (SIM) is defined. This measure quantifies the interleaving of two surfaces as their alignment is refined, putting the qualitative evaluation of “splotchiness,” often used in reference to renderings of the aligned surfaces, onto a solid mathematical footing. The SIM is shown to be superior to mean squared error (i.e. more sensitive to fine scale changes) in controlling the final stages of the alignment process.The authors go on to combine the SIM with Genetic Algorithms (GAs) to develop a robust approach for range image registration. The results confirm that this technique achieves precise surface registration with no need for prealignment, as opposed to methods based on the Iterative Closest Point (ICP) algorithm, the most popular to date. Thorough experimental results including an extensive comparative study are presented and enhanced GA-based approaches to improve the registration still further are proposed. The authors also develop a global multiview registration technique using the GA-based approach. The results show considerable promise in terms of accuracy for 3D modeling.

Product Details

ISBN-13:
9789812561084
Publisher:
World Scientific Publishing Company, Incorporated
Publication date:
12/28/2004
Series:
Series in Machine Perception and Artificial Intelligence
Pages:
176
Product dimensions:
6.20(w) x 9.00(h) x 0.60(d)

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