Marc Spicker, J. Kratt, Diana Arellano, O. Deussen
{"title":"深度感知连贯线条图","authors":"Marc Spicker, J. Kratt, Diana Arellano, O. Deussen","doi":"10.1145/2820903.2820909","DOIUrl":null,"url":null,"abstract":"In this paper we utilize depth information to extend a line drawing algorithm, improving depth perception and object differentiation in large and spatially complex scenes. We consider different scales of features and apply a flow-based morphological filter to the scenes. Based on this two line drawing styles are defined. The proposed algorithm works in real-time and enables users to manipulate the parameter space through instant visual feedback. We evaluated the effectiveness of our method by performing a user study.","PeriodicalId":21720,"journal":{"name":"SIGGRAPH Asia 2015 Technical Briefs","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Depth-aware coherent line drawings\",\"authors\":\"Marc Spicker, J. Kratt, Diana Arellano, O. Deussen\",\"doi\":\"10.1145/2820903.2820909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we utilize depth information to extend a line drawing algorithm, improving depth perception and object differentiation in large and spatially complex scenes. We consider different scales of features and apply a flow-based morphological filter to the scenes. Based on this two line drawing styles are defined. The proposed algorithm works in real-time and enables users to manipulate the parameter space through instant visual feedback. We evaluated the effectiveness of our method by performing a user study.\",\"PeriodicalId\":21720,\"journal\":{\"name\":\"SIGGRAPH Asia 2015 Technical Briefs\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGGRAPH Asia 2015 Technical Briefs\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2820903.2820909\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGGRAPH Asia 2015 Technical Briefs","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2820903.2820909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we utilize depth information to extend a line drawing algorithm, improving depth perception and object differentiation in large and spatially complex scenes. We consider different scales of features and apply a flow-based morphological filter to the scenes. Based on this two line drawing styles are defined. The proposed algorithm works in real-time and enables users to manipulate the parameter space through instant visual feedback. We evaluated the effectiveness of our method by performing a user study.