Coarse-to-fine approximation of range images with bounded error adaptive triangular meshes
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
S P I E - International Society for Optical EngineeringDate
2007Citation
10.1117/1.2731824
Journal of Electronic Imaging 16.2 (2007): 023010
ISSN
1017-9909DOI
10.1117/1.2731824Funded by
This work has been partially supported by the Spanish Ministry of Education and Science under projects TRA2004- 06702/AUT and DPI2004-07993-C03-03. The first author was supported by The Ramón y Cajal Program.Project
Gobierno de España. TRA2004-06702/AUT; Gobierno de España. DPI2004-07993-C03-03Editor's Version
http://dx.doi.org/10.1117/1.2731824Subjects
Informática; TelecomunicacionesNote
Copyright 2007 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibitedRights
Copyright 2007 Society of Photo-Optical Instrumentation EngineersAbstract
A new technique for approximating range images with adaptive triangular meshes ensuring a user-defined approximation error is presented. This technique is based on an efficient coarse-to-fine refinement algorithm that avoids iterative optimization stages. The algorithm first maps the pixels of the given range image to 3D points defined in a curvature space. Those points are then tetrahedralized with a 3D Delaunay algorithm. Finally, an iterative process starts digging up the convex hull of the obtained tetrahedralization, progressively removing the triangles that do not fulfill the specified approximation error. This error is assessed in the original 3D space. The introduction of the aforementioned curvature space makes it possible for both convex and nonconvex object surfaces to be approximated with adaptive triangular meshes, improving thus the behavior of previous coarse-to-fine sculpturing techniques. The proposed technique is evaluated on real range images and compared to two simplification techniques that also ensure a user-defined approximation error: a fine-to-coarse approximation algorithm based on iterative optimization (Jade) and an optimization-free, fine-to-coarse algorithm (Simplification Envelopes).
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Google Scholar:Sappa, Ángel D.
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García García, Miguel Ángel
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