Select the Best Surface Fitting Approach for the Reconstruction of High Quality 3-D Objects from Range-image Data

Applying surface fitting models to reconstruct 3-10 objects with free-form features is widely employed from toy industry to medical surgery. However, reconstruction of free-form surfaces from range-image data always prone to intensive manual operations, and some technical skills are always needed. R...

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Veröffentlicht in:IAENG international journal of computer science 2006-12, Vol.32 (4), p.408-413
Hauptverfasser: Ip, Ralph W L, Yeung, Angela C W, Chan, Felix T S, Lau, Henry C W
Format: Artikel
Sprache:eng
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Zusammenfassung:Applying surface fitting models to reconstruct 3-10 objects with free-form features is widely employed from toy industry to medical surgery. However, reconstruction of free-form surfaces from range-image data always prone to intensive manual operations, and some technical skills are always needed. Recently, research focus on the studies of improving surface reconstruction results to achieve better quality with simple processing procedures. The research aims to report some strategies that provide guidelines to select appropriate surface fitting models for achieving the required quality at the shortest time. The surface fitting models including Extrusion, Revolution, Sweeping, Coons and Loft were detailed examined and compared with their abilities in the reconstruction of primitive 3-D objects. Findings of the research illustrated that the listed fitting models could work well for a specific group of object surfaces. A shorter surface reconstruction time and better fitting result can be achieved from the recommended fitting models. A table categorizes surface fitting models provide the best fitting to various shape primitive 3-D objects. Successfully apply the proposed surface fitting selection approach can simplify intensive learning of various surface modelling tools, and also build up confidence for unskllful designers in the using sophisticated computer-aided surface modelling software.
ISSN:1819-656X
1819-9224