An Information Theory Framework for the Analysis of Scene Complexity

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dc.contributor.authorFeixas, Miquelen_US
dc.contributor.authorDel Acebo, Esteveen_US
dc.contributor.authorBekaert, Philippeen_US
dc.contributor.authorSbert, Mateuen_US
dc.date.accessioned2015-02-16T06:55:00Z
dc.date.available2015-02-16T06:55:00Z
dc.date.issued1999en_US
dc.description.abstractIn this paper we present a new framework for the analysis of scene visibility and radiosity complexity. We introduce a number of complexity measures from information theory quantifying how difficult it is to compute with accuracy the visibility and radiosity in a scene. We define the continuous mutual information as a complexity measure of a scene, independent of whatever discretisation, and discrete mutual information as the complexity of a discretised scene. Mutual information can be understood as the degree of correlation or dependence between all the points or patches of a scene. Thus, low complexity corresponds to low correlation and vice versa. Experiments illustrating that the best mesh of a given scene among a number of alternatives corresponds to the one with the highest discrete mutual information, indicate the feasibility of the approach. Unlike continuous mutual information, which is very cheap to compute, the computation of discrete mutual information can however be quite demanding. We will develop cheap complexity measure estimates and derive practical algorithms from this framework in future work.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume18en_US
dc.identifier.doi10.1111/1467-8659.00331en_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages95-106en_US
dc.identifier.urihttps://doi.org/10.1111/1467-8659.00331en_US
dc.publisherBlackwell Publishers Ltd and the Eurographics Associationen_US
dc.titleAn Information Theory Framework for the Analysis of Scene Complexityen_US
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