Perceptual models of viewpoint preference

Adrian Secord, Jingwan Lu, Adam Finkelstein, Manish Singh, Andrew Nealen

    Research output: Contribution to journalReview articlepeer-review


    The question of what are good views of a 3D object has been addressed by numerous researchers in perception, computer vision, and computer graphics. This has led to a large variety of measures for the goodness of views as well as some special-case viewpoint selection algorithms. In this article, we leverage the results of a large user study to optimize the parameters of a general model for viewpoint goodness, such that the fitted model can predict people's preferred views for a broad range of objects. Our model is represented as a combination of attributes known to be important for view selection, such as projected model area and silhouette length. Moreover, this framework can easily incorporate new attributes in the future, based on the data from our existing study. We demonstrate our combined goodness measure in a number of applications, such as automatically selecting a good set of representative views, optimizing camera orbits to pass through good views and avoid bad views, and trackball controls that gently guide the viewer towards better views.

    Original languageEnglish (US)
    Article number109
    JournalACM Transactions on Graphics
    Issue number5
    StatePublished - Oct 2011


    • Camera control
    • User interfaces
    • User study
    • Viewpoint selection
    • Visual perception

    ASJC Scopus subject areas

    • Computer Graphics and Computer-Aided Design


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