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Open AccessArticle

A Survey of Viewpoint Selection Methods for Polygonal Models

1
Graphics & Imaging Laboratory, University of Girona, Girona 17003, Spain
2
School of Computer Science and Technology, Tianjin University, Tianjin 300350, China
3
Max Planck Institute for Biological Cybernetics, Tuebingen 72076, Germany
4
Department of Brain Cognitive Engineering, Korea University, Seoul 02841, Korea
*
Author to whom correspondence should be addressed.
Entropy 2018, 20(5), 370; https://doi.org/10.3390/e20050370
Received: 24 March 2018 / Revised: 11 May 2018 / Accepted: 11 May 2018 / Published: 16 May 2018
(This article belongs to the Special Issue Information Theory Application in Visualization)
Viewpoint selection has been an emerging area in computer graphics for some years, and it is now getting maturity with applications in fields such as scene navigation, scientific visualization, object recognition, mesh simplification, and camera placement. In this survey, we review and compare twenty-two measures to select good views of a polygonal 3D model, classify them using an extension of the categories defined by Secord et al., and evaluate them against the Dutagaci et al. benchmark. Eleven of these measures have not been reviewed in previous surveys. Three out of the five short-listed best viewpoint measures are directly related to information. We also present in which fields the different viewpoint measures have been applied. Finally, we provide a publicly available framework where all the viewpoint selection measures are implemented and can be compared against each other. View Full-Text
Keywords: visualization; viewpoint selection; entropy; mutual information visualization; viewpoint selection; entropy; mutual information
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Bonaventura, X.; Feixas, M.; Sbert, M.; Chuang, L.; Wallraven, C. A Survey of Viewpoint Selection Methods for Polygonal Models. Entropy 2018, 20, 370.

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