A Survey of Viewpoint Selection Methods for Polygonal Models
dc.contributor.author
dc.date.accessioned
2018-05-29T12:06:48Z
dc.date.available
2018-05-29T12:06:48Z
dc.date.issued
2018-05-16
dc.identifier.uri
dc.description.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
dc.description.sponsorship
This work has been partially funded by grant TIN2016-75866-C3-3-R from the Spanish Government, grant 2017-SGR-1101 from Catalan Government and by the National Natural Science Foundation of China (Nos. 61571439, 61471261 and 61771335)
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
MDPI (Multidisciplinary Digital Publishing Institute)
dc.relation
MINECO/PE 2016-2019/TIN2016-75866-C3-3-R
dc.relation.isformatof
Reproducció digital del document publicat a: https://doi.org/10.3390/e20050370
dc.relation.ispartof
Entropy, 2018, vol. 20, núm. 5, p.370
dc.relation.ispartofseries
Articles publicats (D-IMA)
dc.rights
Attribution 4.0 International
dc.rights.uri
dc.subject
dc.title
A Survey of Viewpoint Selection Methods for Polygonal Models
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.contributor.funder
dc.type.peerreviewed
peer-reviewed
dc.identifier.eissn
1099-4300