摘要：In this article we present an algorithm for the detection of perceptually relevant alignments in 3D point clouds. The algorithm is an extension of the algorithm developed by Lezama et al. [J. Lezama, J-M. Morel, G. Randall, R. Grompone von Gioi, A Contrario 2D Point Alignment Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 37 (3), pp. 499-512, 2015] for the case of sets of 2D points. The algorithm is based on the a contrario detection theory that mathematically formalizes the non-accidentalness principle proposed for perception: an observed structure is relevant if it rarely occurs by chance. This framework has been widely used in different detection tasks and leads to algorithms with a single critical parameter to control the number of false detections.
关键词：point alignment detection; 3D point alignments; a contrario method; Gestalt theory
