{"title":"使用笔画过程自定义绘画渲染样式","authors":"Mingtian Zhao, Song-Chun Zhu","doi":"10.1145/2024676.2024698","DOIUrl":null,"url":null,"abstract":"In this paper, we study the stroke placement problem in painterly rendering, and present a solution named stroke processes, which enables intuitive and interactive customization of painting styles by mapping perceptual characteristics to rendering parameters. Using our method, a user can adjust styles (e.g., Fig.1) easily by controlling these intuitive parameters. Our model and algorithm are capable of reflecting various styles in a single framework, which includes point processes and stroke neighborhood graphs to model the spatial layout of brush strokes, and stochastic reaction-diffusion processes to compute the levels and contrasts of their attributes to match desired statistics. We demonstrate the rendering quality and flexibility of this method with extensive experiments.","PeriodicalId":204343,"journal":{"name":"International Symposium on Non-Photorealistic Animation and Rendering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":"{\"title\":\"Customizing painterly rendering styles using stroke processes\",\"authors\":\"Mingtian Zhao, Song-Chun Zhu\",\"doi\":\"10.1145/2024676.2024698\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study the stroke placement problem in painterly rendering, and present a solution named stroke processes, which enables intuitive and interactive customization of painting styles by mapping perceptual characteristics to rendering parameters. Using our method, a user can adjust styles (e.g., Fig.1) easily by controlling these intuitive parameters. Our model and algorithm are capable of reflecting various styles in a single framework, which includes point processes and stroke neighborhood graphs to model the spatial layout of brush strokes, and stochastic reaction-diffusion processes to compute the levels and contrasts of their attributes to match desired statistics. We demonstrate the rendering quality and flexibility of this method with extensive experiments.\",\"PeriodicalId\":204343,\"journal\":{\"name\":\"International Symposium on Non-Photorealistic Animation and Rendering\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"37\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Non-Photorealistic Animation and Rendering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2024676.2024698\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Non-Photorealistic Animation and Rendering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2024676.2024698","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Customizing painterly rendering styles using stroke processes
In this paper, we study the stroke placement problem in painterly rendering, and present a solution named stroke processes, which enables intuitive and interactive customization of painting styles by mapping perceptual characteristics to rendering parameters. Using our method, a user can adjust styles (e.g., Fig.1) easily by controlling these intuitive parameters. Our model and algorithm are capable of reflecting various styles in a single framework, which includes point processes and stroke neighborhood graphs to model the spatial layout of brush strokes, and stochastic reaction-diffusion processes to compute the levels and contrasts of their attributes to match desired statistics. We demonstrate the rendering quality and flexibility of this method with extensive experiments.