Zhongping Ji , Xianfang Sun , Yu-Wei Zhang , Weiyin Ma , Mingqiang Wei
{"title":"对浅浮雕建模的正常操作","authors":"Zhongping Ji , Xianfang Sun , Yu-Wei Zhang , Weiyin Ma , Mingqiang Wei","doi":"10.1016/j.gmod.2021.101099","DOIUrl":null,"url":null,"abstract":"<div><p><span><span>We introduce a normal-based modeling framework for bas-relief generation and stylization which is motivated by the recent advancement in this topic. Creating bas-relief from normal images has successfully facilitated bas-relief modeling in image space. However, the use of normal images in previous work is restricted to the cut-and-paste or blending operations of layers. These operations simply treat a normal vector as a pixel of a general color image. This paper is intended to extend normal-based methods by processing the normal image from a geometric perspective. Our method can not only generate a new normal image by combining various frequencies of existing normal images and details transferring, but also build bas-reliefs from a single </span>RGB<span> image and its edge-based sketch lines. In addition, we introduce an auxiliary function to represent a smooth base surface or generate a layered global shape. To integrate above considerations into our framework, we formulate the bas-relief generation as a </span></span>variational problem<span> which can be solved by a screened Poisson equation. One important advantage of our method is that it can generate more styles than previous methods and thus it expands the bas-relief shape space. We experimented our method on a range of normal images and it compares favorably to other popular classic and state-of-the-art methods.</span></p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"114 ","pages":"Article 101099"},"PeriodicalIF":2.5000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gmod.2021.101099","citationCount":"0","resultStr":"{\"title\":\"Normal manipulation for bas-relief modeling\",\"authors\":\"Zhongping Ji , Xianfang Sun , Yu-Wei Zhang , Weiyin Ma , Mingqiang Wei\",\"doi\":\"10.1016/j.gmod.2021.101099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span><span>We introduce a normal-based modeling framework for bas-relief generation and stylization which is motivated by the recent advancement in this topic. Creating bas-relief from normal images has successfully facilitated bas-relief modeling in image space. However, the use of normal images in previous work is restricted to the cut-and-paste or blending operations of layers. These operations simply treat a normal vector as a pixel of a general color image. This paper is intended to extend normal-based methods by processing the normal image from a geometric perspective. Our method can not only generate a new normal image by combining various frequencies of existing normal images and details transferring, but also build bas-reliefs from a single </span>RGB<span> image and its edge-based sketch lines. In addition, we introduce an auxiliary function to represent a smooth base surface or generate a layered global shape. To integrate above considerations into our framework, we formulate the bas-relief generation as a </span></span>variational problem<span> which can be solved by a screened Poisson equation. One important advantage of our method is that it can generate more styles than previous methods and thus it expands the bas-relief shape space. We experimented our method on a range of normal images and it compares favorably to other popular classic and state-of-the-art methods.</span></p></div>\",\"PeriodicalId\":55083,\"journal\":{\"name\":\"Graphical Models\",\"volume\":\"114 \",\"pages\":\"Article 101099\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2021-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.gmod.2021.101099\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Graphical Models\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1524070321000047\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Graphical Models","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1524070321000047","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
We introduce a normal-based modeling framework for bas-relief generation and stylization which is motivated by the recent advancement in this topic. Creating bas-relief from normal images has successfully facilitated bas-relief modeling in image space. However, the use of normal images in previous work is restricted to the cut-and-paste or blending operations of layers. These operations simply treat a normal vector as a pixel of a general color image. This paper is intended to extend normal-based methods by processing the normal image from a geometric perspective. Our method can not only generate a new normal image by combining various frequencies of existing normal images and details transferring, but also build bas-reliefs from a single RGB image and its edge-based sketch lines. In addition, we introduce an auxiliary function to represent a smooth base surface or generate a layered global shape. To integrate above considerations into our framework, we formulate the bas-relief generation as a variational problem which can be solved by a screened Poisson equation. One important advantage of our method is that it can generate more styles than previous methods and thus it expands the bas-relief shape space. We experimented our method on a range of normal images and it compares favorably to other popular classic and state-of-the-art methods.
期刊介绍:
Graphical Models is recognized internationally as a highly rated, top tier journal and is focused on the creation, geometric processing, animation, and visualization of graphical models and on their applications in engineering, science, culture, and entertainment. GMOD provides its readers with thoroughly reviewed and carefully selected papers that disseminate exciting innovations, that teach rigorous theoretical foundations, that propose robust and efficient solutions, or that describe ambitious systems or applications in a variety of topics.
We invite papers in five categories: research (contributions of novel theoretical or practical approaches or solutions), survey (opinionated views of the state-of-the-art and challenges in a specific topic), system (the architecture and implementation details of an innovative architecture for a complete system that supports model/animation design, acquisition, analysis, visualization?), application (description of a novel application of know techniques and evaluation of its impact), or lecture (an elegant and inspiring perspective on previously published results that clarifies them and teaches them in a new way).
GMOD offers its authors an accelerated review, feedback from experts in the field, immediate online publication of accepted papers, no restriction on color and length (when justified by the content) in the online version, and a broad promotion of published papers. A prestigious group of editors selected from among the premier international researchers in their fields oversees the review process.