Editable Parametric Dense Foliage from 3D Capture

P. Beardsley, G. Chaurasia
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引用次数: 9

Abstract

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.
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可编辑的参数密集树叶从3D捕获
本文提出了一种计算浓密树叶参数化模型的算法。我们的工作指导原则是自动重建和紧凑的艺术家友好的表现。我们使用贝塞尔补丁来模拟树叶表面,我们从图像和密集树叶的点云中计算。我们提出了一种从颜色和深度数据中分割单个叶子的算法。然后,我们使用非线性优化从分割的叶点云重建贝塞尔表示。与以前的工作不同,我们不需要实验室扫描样本或用户干预。我们还演示了直观的操纵器来编辑重建的参数模型。我们相信我们的工作是朝着使捕获的数据更容易被艺术家用于树叶建模迈出的一步。
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