View publication

Title SHREC 2022: Fitting and Recognition of Simple Geometric Primitives on Point Clouds
Authors Chiara Romanengo, Andrea Raffo, Silvia Biasotti, Bianca Falcidieno, Vlassis Fotis, Ioannis Romanelis, Eleftheria Psathas, Konstantinos Moustakas, Iván Sipirán, Quang-Thuc Nguyen, Chi-Bien Chu, Khoi-Nguyen Nguyen-Ngoc, Dinh-Khoi Vo, Tuan-An To, Nham-Tan Nguyen, Nhat-Quynh Le-Pham, Hai-Dang Nguyen, Minh-Triet Tran, Yifan Qie, Nabil Anwer
Publication date October 2022
Abstract This paper presents the methods that have participated in
SHREC 2022 track on the fitting and recognition of simple geometric
primitives on point clouds. As simple primitives we mean the classical
surface primitives derived from constructive solid geometry, i.e., planes,
spheres, cylinders, cones and tori. The aim of the track is to evaluate the
quality of automatic algorithms for fitting and recognizing geometric
primitives on point clouds. Specifically, the goal is to identify, for each
point cloud, its primitive type and some geometric descriptors. For this
purpose, we created a synthetic dataset, divided into a training set and a
test set, containing segments perturbed with different kinds of point cloud
artifacts. Among the six participants to this track, two are based on direct
methods, while four are either fully based on deep learning or combine
direct and neural approaches. The performance of the methods is evaluated
using various classification and approximation measures.
Pages 32-49
Volume 107
Journal name Computers & Graphics
Publisher Elsevier Science (Amsterdam, The Netherlands)
Reference URL View reference page