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Automatic generation of subdivision surface head models from point cloud data

机译:从点云数据自动生成细分表面头模型

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An automatic procedure is presented to generate a multiresolution head model from sampled surface data. A generic control mesh serves as the starting point for a fitting algorithm that approximates the points in an unstructured set of surface samples, e.g. a point cloud obtained directly from range scans of an individual. A hierarchical representation of the model is generated by repeated refinement using subdivision rules and measuring displacements to the input data. Key features of our method are the frilly automated construction process, the ability to deal with noisy and incomplete input data, and no requirement for further processing of the scan data after registering the range images into a single point cloud.
机译:提出了一种自动过程以从采样的表面数据生成多分辨率头模型。通用控制网格用作拟合算法的起点,其近似于非结构化的表面样本组中的点,例如,直接从个人的范围扫描获得的点云。使用细分规则和测量输入数据的位移来生成模型的分层表示。我们的方法的主要特点是Frilly自动化施工过程,处理噪声和不完整的输入数据的能力,并且不需要在将范围图像注册到单点云中后进一步处理扫描数据。

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