We present a texture synthesis scheme based on neighborhood matching, with contributions in two areas: parallelism and control.\u00a0 Our scheme defines an infinite, deterministic, aperiodic texture, from which windows can be computed in real-time on a GPU.\u00a0 We attain high-quality synthesis using a new analysis structure called the Gaussian stack, together with a coordinate upsampling step and a subpass correction approach.\u00a0 Texture variation is achieved by multiresolution jittering of exemplar coordinates.\u00a0 Combined with the local support of parallel synthesis, the jitter enables intuitive user controls including multiscale randomness, spatial modulation over both exemplar and output, feature dragand-drop, and periodicity constraints.\u00a0 We also introduce synthesis magnification, a fast method for amplifying coarse synthesis results to higher resolution.<\/p>\n","protected":false},"excerpt":{"rendered":"
We present a texture synthesis scheme based on neighborhood matching, with contributions in two areas: parallelism and control.\u00a0 Our scheme defines an infinite, deterministic, aperiodic texture, from which windows can be computed in real-time on a GPU.\u00a0 We attain high-quality synthesis using a new analysis structure called the Gaussian stack, together with a coordinate upsampling […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"ACM Trans. Graph.","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"ACM Trans. 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