{"id":421839,"date":"2017-08-25T09:14:49","date_gmt":"2017-08-25T16:14:49","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=421839"},"modified":"2018-10-16T20:17:45","modified_gmt":"2018-10-17T03:17:45","slug":"filtering-rendering-resolution-dependent-reflectance-models","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/filtering-rendering-resolution-dependent-reflectance-models\/","title":{"rendered":"Filtering and Rendering of Resolution-Dependent Reflectance Models"},"content":{"rendered":"
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The reflectance of a surface depends upon the resolution at which it is imaged. In this work, we propose to represent this resolution-dependent reflectance as a mixture of multiple conventional reflectance models and present a framework for efficiently rendering the reflectance effects of such mixture models over different resolutions. To rapidly determine reflectance at runtime with respect to resolution, we record the mixture model parameters at multiple resolution levels in mipmaps and propose a technique to minimize aliasing in the filtering of these mipmaps. This framework can be applied to several widely used parametric reflectance models and can be implemented in graphics hardware for real-time processing, using a presented hardware-accelerated technique for nonlinear filtering of mixture model parameters. In addition, shadowing and masking effects can be included into this framework to increase the realism of rendering. With this mixture model filtering and rendering framework, our system can efficiently render the fine reflectance detail that is customarily disregarded in conventional rendering methods.<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n<\/div>\n<\/div>\n<\/section>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

The reflectance of a surface depends upon the resolution at which it is imaged. In this work, we propose to represent this resolution-dependent reflectance as a mixture of multiple conventional reflectance models and present a framework for efficiently rendering the reflectance effects of such mixture models over different resolutions. To rapidly determine reflectance at runtime […]<\/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":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"2","msr_journal":"IEEE Transactions on Visualization and Computer 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