In this paper we investigate a local surface approximation, the Weighted Quasi Interpolant Spline Approximation (wQISA), specifically designed for large and noisy point clouds. We briefly describe the properties of the wQISA representation and introduce a novel data-driven implementation, which combines prediction capability and complexity efficiency. We provide an extended comparative analysis with other continuous approximations on real data, including different types of surfaces and levels of noise, such as 3D models, terrain data and digital environmental data.

中文翻译：

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用于点云近似的数据驱动的准插值样条曲面

在本文中，我们研究了一种局部表面近似，即加权准插值样条近似 (wQISA)，专为大型和嘈杂的点云设计。我们简要描述了 wQISA 表示的属性，并介绍了一种新的数据驱动实现，它结合了预测能力和复杂性效率。我们提供了与真实数据的其他连续近似值的扩展比较分析，包括不同类型的表面和噪声级别，例如 3D 模型、地形数据和数字环境数据。