Realistic Procedural Plant Modeling from Multiple View Images
Jianwei Guo; Shibiao Xu; Dong-Ming Yan; Zhanglin Cheng; Marc Jaeger; Xiaopeng Zhang
2018-09-24
发表期刊IEEE Transactions on Visualization and Computer Graphics
卷号xx期号:xx页码:xx
摘要In this paper, we describe a novel procedural modeling technique for generating realistic plant models from multi-view photographs. The realism is enhanced via visual and spatial information acquired from images. In contrast to previous approaches that heavily rely on user interaction to segment plants or recover branches in images, our method automatically estimates an accurate depth map of each image and extracts a 3D dense point cloud by exploiting an efficient stereophotogrammetry approach. Taking this point cloud as a soft constraint, we fit a parametric plant representation to simulate the plant growth progress. In this way, we are able to combine real data (photos and 3D point clouds) analysis with rule-based procedural plant modeling. We demonstrate the robustness of the proposed approach by modeling a variety of plants with complex branching structures and significant self-occlusions. We also demonstrate that the proposed framework can be used to reconstruct ground-covering plants, such as bushes and shrubs which have gained little attention in the literature. The effectiveness of our approach is validated by visually and quantitatively comparing with the state-of-the-art approaches.; In this paper, we describe a novel procedural modeling technique for generating realistic plant models from multi-view photographs. The realism is enhanced via visual and spatial information acquired from images. In contrast to previous approaches that heavily rely on user interaction to segment plants or recover branches in images, our method automatically estimates an accurate depth map of each image and extracts a 3D dense point cloud by exploiting an efficient stereophotogrammetry approach. Taking this point cloud as a soft constraint, we fit a parametric plant representation to simulate the plant growth progress. In this way, we are able to combine real data (photos and 3D point clouds) analysis with rule-based procedural plant modeling. We demonstrate the robustness of the proposed approach by modeling a variety of plants with complex branching structures and significant self-occlusions. We also demonstrate that the proposed framework can be used to reconstruct ground-covering plants, such as bushes and shrubs which have gained little attention in the literature. The effectiveness of our approach is validated by visually and quantitatively comparing with the state-of-the-art approaches.
关键词Three-dimensional Displays Solid Modeling Computational Modeling Image Reconstruction Shape Geometry Vegetation
DOI10.1109/TVCG.2018.2869784
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/21686
专题模式识别国家重点实验室_多媒体计算与图形学
通讯作者Dong-Ming Yan
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GB/T 7714
Jianwei Guo,Shibiao Xu,Dong-Ming Yan,et al. Realistic Procedural Plant Modeling from Multiple View Images[J]. IEEE Transactions on Visualization and Computer Graphics,2018,xx(xx):xx.
APA Jianwei Guo,Shibiao Xu,Dong-Ming Yan,Zhanglin Cheng,Marc Jaeger,&Xiaopeng Zhang.(2018).Realistic Procedural Plant Modeling from Multiple View Images.IEEE Transactions on Visualization and Computer Graphics,xx(xx),xx.
MLA Jianwei Guo,et al."Realistic Procedural Plant Modeling from Multiple View Images".IEEE Transactions on Visualization and Computer Graphics xx.xx(2018):xx.
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