基于icp的位姿测量几何特征评估新方法:连续体形状约束分析

D. McTavish, G. Okouneva
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引用次数: 8

摘要

本文提出了最近点约束分析的一种推广方法,称为连续体形状约束分析(CSCA),该方法可用于评估整个物体或物体特征对距离数据扫描和随后的姿态估计的适用性。“定向CSCA”(D-CSCA)被提出通过ICP(迭代最近点)算法家族专门解决姿态估计精度问题。采用基于噪声放大指数(NAI)的约束分析。在D-CSCA配方中,底层形状配准的连续性质使得所得到的梯度矩阵及其NAI作为特征的纯粹属性,依赖于视点,但独立于观察仪器。
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A New Approach to Geometrical Feature Assessment for ICP-Based Pose Measurement: Continuum Shape Constraint Analysis
This paper presents a generalization of closest- point constraint analysis called continuum shape constraint analysis (CSCA) that can be used to assess the suitability of whole objects or object features for range data scanning and subsequent pose estimation. "Directional CSCA" (D-CSCA) is proposed to specifically address pose estimation accuracy via the ICP (iterated closest-point) family of algorithms. Constraint analysis based on noise amplification index (NAI) is used. In the D-CSCA formulation, the continuum nature of the underlying shape registration renders the resulting gradient matrix and NAI thereof as pure properties of the feature, dependent on viewpoint but independent of the viewing instrument.
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