GA based Adaptive Sampling for Image-based Walkthrough

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dc.contributor.authorLee, Dong Hoonen_US
dc.contributor.authorKim, Jong Ryulen_US
dc.contributor.authorJung, Soon Kien_US
dc.contributor.editorMing Lin and Roger Hubbolden_US
dc.date.accessioned2014-01-27T10:47:25Z
dc.date.available2014-01-27T10:47:25Z
dc.date.issued2006en_US
dc.description.abstractThis paper presents an adaptive sampling method for image-based walkthrough. Our goal is to select minimal sets from the initially dense sampled data set, while guaranteeing a visual correct view from any position in any direction in walkthrough space. For this purpose we formulate the covered region for sampling criteria and then regard the sampling problem as a set covering problem. We estimate the optimal set using Genetic algorithm, and show the efficiency of the proposed method with several experiments.en_US
dc.description.seriesinformationEurographics Symposium on Virtual Environmentsen_US
dc.identifier.isbn3-905673-33-9en_US
dc.identifier.issn1727-530Xen_US
dc.identifier.urihttps://doi.org/10.2312/EGVE/EGVE06/135-142en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Virtual Realityen_US
dc.titleGA based Adaptive Sampling for Image-based Walkthroughen_US
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EGVE06: 12th Eurographics Symposium on Virtual Environments