Reliable 3D surface acquisition, registration and validation using statistical error models

J. Guehring
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引用次数: 56

Abstract

We present a complete data acquisition and processing chain for the reliable inspection of industrial parts considering anisotropic noise. Data acquisition is performed with a stripe projection system that was modeled and calibrated using photogrammetric techniques. Covariance matrices are attached individually to points during 3D coordinate computation. Different datasets are registered using a new multi-view registration technique. In the validation step, the registered datasets are compared with the CAD model to verify that the measured part meets its specification. While previous methods have only considered the geometrical discrepancies between the sensed part and its CAD model, we also consider statistical information to decide whether the differences are significant.
可靠的三维表面采集,注册和验证使用统计误差模型
我们提出了一个完整的数据采集和处理链,用于考虑各向异性噪声的工业零件的可靠检测。数据采集是通过使用摄影测量技术建模和校准的条纹投影系统进行的。在三维坐标计算中,协方差矩阵被单独附加到点上。不同的数据集使用新的多视图注册技术进行注册。在验证步骤中,将注册数据集与CAD模型进行比较,以验证被测量部件是否符合其规格。虽然以前的方法只考虑了被测部件与其CAD模型之间的几何差异,但我们也考虑了统计信息来决定差异是否显著。
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