A survey of viewpoint selection methods for polygonal models

Xavier Bonaventura, Miquel Feixas, Mateu Sbert, Lewis Chuang, Christian Wallraven

    Research output: Contribution to journalArticlepeer-review

    34 Citations (Scopus)

    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.

    Original languageEnglish
    Article number370
    JournalEntropy
    Volume20
    Issue number5
    DOIs
    Publication statusPublished - 2018 May 16

    Bibliographical note

    Publisher Copyright:
    © 2018 by the authors.

    Keywords

    • Entropy
    • Mutual information
    • Viewpoint selection
    • Visualization

    ASJC Scopus subject areas

    • Information Systems
    • Mathematical Physics
    • Physics and Astronomy (miscellaneous)
    • Electrical and Electronic Engineering

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