CASIA OpenIR  > 复杂系统认知与决策实验室  > 高效智能计算与学习
Layered leaf texturing using structure-guided model
Qian, Yinling1; Shi, Jian2; Sun, Hanqiu3; Ma, Lei4; Chen, Yanyun5; Wang, Qiong6; Heng, Pheng-Ann3,6
Source PublicationGRAPHICAL MODELS
ISSN1524-0703
2019-05-01
Volume103Pages:10
Corresponding AuthorWang, Qiong(wangqiong@siat.ac.cn)
AbstractGenerating natural textures is a challenging task in graphics and virtual reality. Leaf texture is an important part of natural textures. Different from many other textures with repetitive and random patterns, leaves are closely related to its botanic structures, especially veins. Appearing in forms of foliages in the wild, the variety of leaf textures produces the realism of virtual scenes. In this paper, we propose a novel leaf-texturing method that models the inherent relevance between structural features and pattern distributions. Based on the structure-guided model, we design an example-based algorithm to extract and generate leaf textures depending on venation structures. Global variations and local details are processed separately for multi-scale texture features. Experiments show that our model produces visually plausible leaf textures with variations, which can be easily applied to many other applications, including texture transfer between different leaf structures, aging effect and texture editing.
KeywordLeaf texturing Texture synthesis Procedural noise
DOI10.1016/j.gmod.2019.101029
WOS KeywordVISUALIZATION
Indexed BySCI
Language英语
Funding ProjectShenzhen Science and Technology Program[JSGG20170414112714341] ; Shenzhen Science and Technology Program[JCYJ20170413162617606] ; Shenzhen Science and Technology Program[JCYJ20170302153015013] ; Natural Science Foundation of China[61802386] ; Natural Science Foundation of China[61602183] ; Shenzhen Science and Technology Program[JSGG20170414112714341] ; Shenzhen Science and Technology Program[JCYJ20170413162617606] ; Shenzhen Science and Technology Program[JCYJ20170302153015013] ; Natural Science Foundation of China[61802386] ; Natural Science Foundation of China[61602183]
Funding OrganizationShenzhen Science and Technology Program ; Natural Science Foundation of China
WOS Research AreaComputer Science
WOS SubjectComputer Science, Software Engineering
WOS IDWOS:000477696200008
PublisherACADEMIC PRESS INC ELSEVIER SCIENCE
Sub direction classification图像视频处理与分析
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/27821
Collection复杂系统认知与决策实验室_高效智能计算与学习
Corresponding AuthorWang, Qiong
Affiliation1.Chinese Acad Sci, Shenzhen Inst Adv Technol, CAS Key Lab Human Machine Intelligence Synergy Sy, Shenzhen, Peoples R China
2.Chinese Acad Sci, Inst Automat, NLPR, Beijing, Peoples R China
3.Chinese Univ Hong Kong, Hong Kong, Peoples R China
4.Peking Univ, Beijing, Peoples R China
5.Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing, Peoples R China
6.Chinese Acad Sci, Shenzhen Inst Adv Technol, Guangdong Prov Key Lab Comp Vis & Virtual Real Te, Shenzhen, Peoples R China
Recommended Citation
GB/T 7714
Qian, Yinling,Shi, Jian,Sun, Hanqiu,et al. Layered leaf texturing using structure-guided model[J]. GRAPHICAL MODELS,2019,103:10.
APA Qian, Yinling.,Shi, Jian.,Sun, Hanqiu.,Ma, Lei.,Chen, Yanyun.,...&Heng, Pheng-Ann.(2019).Layered leaf texturing using structure-guided model.GRAPHICAL MODELS,103,10.
MLA Qian, Yinling,et al."Layered leaf texturing using structure-guided model".GRAPHICAL MODELS 103(2019):10.
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