Editable Parametric Dense Foliage from 3D Capture

被引:9
作者
Chaurasia, Gaurav [1 ]
Beardsley, Paul [1 ]
机构
[1] Disney Res Zurich, Zurich, Switzerland
来源
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) | 2017年
关键词
RECONSTRUCTION; TREES; SUPERPIXELS; MORPHOLOGY; LEAVES; MODEL;
D O I
10.1109/ICCV.2017.567
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present an algorithm to compute parametric models of dense foliage. The guiding principles of our work are automatic reconstruction and compact artist friendly representation. We use Bezier patches to model leaf surface, which we compute from images and point clouds of dense foliage. We present an algorithm to segment individual leaves from colour and depth data. We then reconstruct the Bezier representation from segmented leaf points clouds using non-linear optimisation. Unlike previous work, we do not require laboratory scanned exemplars or user intervention. We also demonstrate intuitive manipulators to edit the reconstructed parametric models. We believe our work is a step towards making captured data more accessible to artists for foliage modelling.
引用
收藏
页码:5315 / 5324
页数:10
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