CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
Tree Branch Level of Detail Models for Forest Navigation
Zhang, Xiaopeng1; Bao, Guanbo1; Meng, Weiliang1; Jaeger, Marc2,3; Li, Hongjun1,4; Deussen, Oliver5,6; Chen, Baoquan7
AbstractWe present a level of detail (LOD) method designed for tree branches. It can be combined with methods for processing tree foliage to facilitate navigation through large virtual forests. Starting from a skeletal representation of a tree, we fit polygon meshes of various densities to the skeleton while the mesh density is adjusted according to the required visual fidelity. For distant models, these branch meshes are gradually replaced with semi-transparent lines until the tree recedes to a few lines. Construction of these complete LOD models is guided by error metrics to ensure smooth transitions between adjacent LOD models. We then present an instancing technique for discrete LOD branch models, consisting of polygon meshes plus semi-transparent lines. Line models with different transparencies are instanced on the GPU by merging multiple tree samples into a single model. Our technique reduces the number of draw calls in GPU and increases rendering performance. Our experiments demonstrate that large-scale forest scenes can be rendered with excellent detail and shadows in real time.
KeywordLevel Of Detail Virtual Forests Real Time Branch Models Simplification i 3 3 [Computer Graphics]: Picture Image Generationline And Curve Generation
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationNational Natural Science Foundation of China(61331018 ; National High Technology Research and Development Program of China(2015AA016402) ; National Foreign 1000 Talent Plan(WQ201344000169) ; Leading Talents of Guangdong Program(00201509) ; 61571439 ; 61571400 ; 61561003)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Software Engineering
WOS IDWOS:000417496200028
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Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, NLPR LIAMA, Inst Automat, Beijing, Peoples R China
2.Cirad, AMAP, Montpellier, France
3.Montpellier Univ, LIRMM ICAR, Montpellier, France
4.Beijing Forestry Univ, Beijing, Peoples R China
5.Chinese Acad Sci, VCC, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China
6.Univ Konstanz, Constance, Germany
7.Shandong Univ, Jinan, Shandong, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Xiaopeng,Bao, Guanbo,Meng, Weiliang,et al. Tree Branch Level of Detail Models for Forest Navigation[J]. COMPUTER GRAPHICS FORUM,2017,36(8):402-417.
APA Zhang, Xiaopeng.,Bao, Guanbo.,Meng, Weiliang.,Jaeger, Marc.,Li, Hongjun.,...&Chen, Baoquan.(2017).Tree Branch Level of Detail Models for Forest Navigation.COMPUTER GRAPHICS FORUM,36(8),402-417.
MLA Zhang, Xiaopeng,et al."Tree Branch Level of Detail Models for Forest Navigation".COMPUTER GRAPHICS FORUM 36.8(2017):402-417.
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