“Seeing is Believing: Reality Perception in Modeling, Rendering, and Animation” by Chalmers, McNamara, Daly, Myszkowski, Rushmeier, et al. …

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Entry Number: 21

Title:

    Seeing is Believing: Reality Perception in Modeling, Rendering, and Animation

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Abstract:


    Prerequisites
    Appreciation of the need for perception evaluation. No prior knowledge of metrics is assumed, although knowledge of human vision and image-quality metrics may be an advantage.

    Topics
    The nature of images; relevant issues in human visual perception and their investigation using psychophysical methods; computational models of perception including spatial-frequency and orientation channels and visual masking; computational metrics including visual difference predictors, the Sarnoff model, and animation quality metrics; and psychophysical evaluation of image quality.

    Description
    Advances in image synthesis techniques allow very precise simulation of light-energy distribution in a scene. Unfortunately, this does not ensure that the displayed image will have a high-fidelity visual appearance. This course addresses techniques to compare real and synthetic images, and identify important visual system characteristics. The ultimate result: significantly reduced rendering times. Case studies involving both static and dynamic images are presented, and their different perception-metric requirements are compared and contrasted.

     


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