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Reconstructing 3D Tree Models Using Motion Capture and Particle Flow

机译:使用运动捕捉和粒子流重建3D树模型

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Recovering tree shape from motion capture data is a first step toward efficient and accurate animation of trees in wind using motion capture data. Existing algorithms for generating models of tree branching structures for image synthesis in computer graphics are not adapted to the unique data set provided by motion capture. We present a method for tree shape reconstruction using particle flow on input data obtained from a passive optical motion capture system. Initial branch tip positions are estimated from averaged and smoothed motion capture data. Branch tips, as particles, are also generated within a bounding space defined by a stack of bounding boxes or a convex hull. The particle flow, starting at branch tips within the bounding volume under forces, creates tree branches. The forces are composed of gravity, internal force, and external force. The resulting shapes are realistic and similar to the original tree crown shape. Several tunable parameters provide control over branch shape and arrangement.
机译:从运动捕获数据中恢复树的形状是使用运动捕获数据向风中的树木进行高效,准确动画的第一步。现有的用于生成用于计算机图形学中的图像合成的树状分支结构模型的算法不适用于运动捕捉所提供的唯一数据集。我们提出了一种使用从无源光学运动捕获系统获得的输入数据上的粒子流进行树形重构的方法。初始分支尖端位置是根据平均和平滑的运动捕获数据估算的。分支尖端(作为粒子)也会在由边界框或凸包的堆栈定义的边界空间内生成。在力的作用下,粒子流从边界体积内的分支尖端开始,创建了树枝。力由重力,内力和外力组成。生成的形状逼真且类似于原始树冠形状。几个可调参数可控制分支的形状和排列。

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