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An approach of adaptive acquisition and modeling for free-form surface with structured-light vision sensor

机译:具有结构光视觉传感器的自由形式自适应采集与建模的方法

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Rapid and high precision data acquisition methodology from coordinate components with free-form surface and geometrical model can be implemented widely. Typical application covers part localization, automatic calibration and reverse engineering. Integrated structured light vision sensor with CMM (Coordinate Measurement Machine) enhances the highprecision coordinate measurement capability. In this paper a curvature-based adaptive sampling approach and the evaluating index for the sampling precision are presented. The matching and subdividing algorithm for generating matrix-type mesh data from sample points is described. The methodology to register and merge the measured data from multiple viewpoints to model the free-form surface is also presented. Based on the given initial coordinate rotation matrix R and transformation vector T, the different viewpoints can be translated into a unique frame of reference. By introducing special coordinate of 3D space, the registered data is divided into mesh, which cover the whole surface of object. An application example for shoe modeling is described to illustrate the advantages
机译:可以广泛实现从具有自由形状和几何模型的坐标组件的快速和高精度数据采集方法。典型应用涵盖零件定位,自动校准和逆向工程。具有CMM(坐标测量机)的集成结构光视图传感器增强了高精度坐标测量功能。本文介绍了一种基于曲率的自适应采样方法和用于采样精度的评估索引。描述了从采样点生成矩阵类型网状数据的匹配和细分算法。还提出了从多个视点注册和合并测量数据以模拟自由形式表面的方法。基于给定的初始坐标旋转矩阵R和转换向量T,可以将不同的视点转换成独特的参考帧。通过引入3D空间的特殊坐标,将注册数据分成网格,覆盖物体的整个表面。描述了鞋造型的应用示例来说明优点

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