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  A Survey of Viewpoint Selection Methods for Polygonal Models

Bonaventura, X., Feixas, M., Sbert, M., Chuang, L., & Wallraven, C. (2018). A Survey of Viewpoint Selection Methods for Polygonal Models. Entropy, 20(5): 370, pp. 1-22. doi:10.3390/e20050370.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-7F71-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-7F72-1
Genre: Journal Article

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http://www.mdpi.com/1099-4300/20/5/370/pdf (Publisher version)
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 Creators:
Bonaventura, X, Author
Feixas, M, Author
Sbert, M, Author
Chuang, L1, 2, Author              
Wallraven, C, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: 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.

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 Dates: 2018-05
 Publication Status: Published in print
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 Identifiers: DOI: 10.3390/e20050370
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Title: Entropy
Source Genre: Journal
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Pages: - Volume / Issue: 20 (5) Sequence Number: 370 Start / End Page: 1 - 22 Identifier: -