文章基本信息

标题：Signature Extraction from 3D Point Clouds using Frame Theory for Environmental Modeling
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作者：Fabio Martino ; Cosimo Patruno ; Roberto Marani 等
期刊名称：International Journal on Smart Sensing and Intelligent Systems
印刷版ISSN：1178-5608
出版年度：2020
卷号：7
期号：5
页码：1-6
DOI：10.21307/ijssis-2019-071
出版社：Massey University
摘要：In this paper a method based on the well-known frame theory is presented for the identification and classification of objects inside a scene. Three-dimensional (3D) point clouds have been firstly acquired using a laser triangulation system exploiting a high resolution camera, in order to derive accurate datasets for the method validation. The method performs a quadratic fit on the acquired samples and then extracts local curvatures from the analytical reconstructed surfaces. Such information is referred to a vocabulary of curvatures, created making use of the frame basis. Meaningful signatures can be finally analyzed to derive the recurrences of objects in the investigated scene. Specifically, by fixing a threshold value ζ, similarities can be estimated and thus objects can be recognized. Results prove the capability of the method to distinguish surface properties among several objects, validating this algorithm against the contributions of the measurement noise.
其他关键词：Object Recognition; Mean and Gaussian Curvatures; Frame Theory; Robot Pose Estimation.