Generalized Stochastic Sampling Method for Visualization and Investigation of Implicit Surfaces

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dc.contributor.authorTanaka, Satoshien_US
dc.contributor.authorShibata, Akihiroen_US
dc.contributor.authorYamamoto, Hiroakien_US
dc.contributor.authorKotsuru, Hisakiyoen_US
dc.date.accessioned2015-02-16T11:06:05Z
dc.date.available2015-02-16T11:06:05Z
dc.date.issued2001en_US
dc.description.abstractRecently we proposed the stochastic sampling method (SSM), which can numerically generate sample points on complicated implicit surfaces quickly and uniformly. In this paper we generalize the method in two aspects: (1) We introduce two kinds of boundary conditions, so that we can sample a finite part of an open surface spreading infinitely. (2) We generalize the stochastic differential equation used in the SSM, so that its solutions can satisfy plural constraint conditions simultaneously. The first generalization enables us to visualize cut views of open surfaces. The second generalization enables us to visualize intersections of static and moving implicit surfaces, which leads to detailed investigation of intersections and other interesting applications such as visualization of contour maps.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume20en_US
dc.identifier.doi10.1111/1467-8659.00528en_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages359-367en_US
dc.identifier.urihttps://doi.org/10.1111/1467-8659.00528en_US
dc.publisherBlackwell Publishers Ltd and the Eurographics Associationen_US
dc.titleGeneralized Stochastic Sampling Method for Visualization and Investigation of Implicit Surfacesen_US
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