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    Rao-Blackwellized Importance Sampling of Camera Parameters from Simple User Input with Visibility Preprocessing in Line Space

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    Date
    2006-06
    Author
    Quennesson, Kevin
    Dellaert, Frank
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    Abstract
    Users know what they see before where they are: it is more natural to talk about high level visibility information ("I see such object") than about one's location or orientation. In this paper we introduce a method to find in 3D worlds a density of viewpoints of camera locations from high level visibility constraints on objects in this world. Our method is based on Rao-Blackwellized importance sampling. For efficiency purposes, the proposal distribution used for sampling is extracted from a visibility preprocessing technique adapted from computer graphics. We apply the method for finding in a 3D city model of Atlanta the virtual locations of real-world cameras and viewpoints.
    URI
    http://hdl.handle.net/1853/38542
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    • Computational Perception & Robotics [213]
    • Computational Perception & Robotics Publications [213]

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