An adaptive point sampler on a regular lattice

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AHMED, Abdalla G. M., Till NIESE, Hui HUANG, Oliver DEUSSEN, 2017. An adaptive point sampler on a regular lattice. In: ACM Transactions on Graphics : TOG. 36(4), 138. ISSN 0730-0301. eISSN 1557-7368. Available under: doi: 10.1145/3072959.3073588

@article{Ahmed2017-07-20adapt-40291, title={An adaptive point sampler on a regular lattice}, year={2017}, doi={10.1145/3072959.3073588}, number={4}, volume={36}, issn={0730-0301}, journal={ACM Transactions on Graphics : TOG}, author={Ahmed, Abdalla G. M. and Niese, Till and Huang, Hui and Deussen, Oliver}, note={Article Number: 138} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dcterms:rights rdf:resource=""/> <dc:creator>Ahmed, Abdalla G. M.</dc:creator> <dspace:isPartOfCollection rdf:resource=""/> <bibo:uri rdf:resource=""/> <dc:creator>Huang, Hui</dc:creator> <dcterms:hasPart rdf:resource=""/> <dspace:hasBitstream rdf:resource=""/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:title>An adaptive point sampler on a regular lattice</dcterms:title> <dc:language>eng</dc:language> <dc:contributor>Deussen, Oliver</dc:contributor> <dc:rights>terms-of-use</dc:rights> <dc:creator>Deussen, Oliver</dc:creator> <dcterms:issued>2017-07-20</dcterms:issued> <dc:creator>Niese, Till</dc:creator> <dc:contributor>Huang, Hui</dc:contributor> <dcterms:isPartOf rdf:resource=""/> <dc:date rdf:datatype="">2017-10-10T13:12:06Z</dc:date> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dcterms:abstract xml:lang="eng">We present a framework to distribute point samples with controlled spectral properties using a regular lattice of tiles with a single sample per tile. We employ a word-based identification scheme to identify individual tiles in the lattice. Our scheme is recursive, permitting tiles to be subdivided into smaller tiles that use the same set of IDs. The corresponding framework offers a very simple setup for optimization towards different spectral properties. Small lookup tables are sufficient to store all the information needed to produce different point sets. For blue noise with varying densities, we employ the bit-reversal principle to recursively traverse sub-tiles. Our framework is also capable of delivering multi-class blue noise samples. It is well-suited for different sampling scenarios in rendering, including area-light sampling (uniform and adaptive), and importance sampling. Other applications include stippling and distributing objects.</dcterms:abstract> <dc:contributor>Ahmed, Abdalla G. M.</dc:contributor> <dcterms:available rdf:datatype="">2017-10-10T13:12:06Z</dcterms:available> <dc:contributor>Niese, Till</dc:contributor> </rdf:Description> </rdf:RDF>

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