Lidar iris for loop-closure detection

Y Wang, Z Sun, CZ Xu, SE Sarma… - 2020 IEEE/RSJ …, 2020 - ieeexplore.ieee.org
In this paper, a global descriptor for a LiDAR point cloud, called LiDAR Iris, is proposed for
fast and accurate loop-closure detection. A binary signature image can be obtained for each …

Dcl-slam: A distributed collaborative lidar slam framework for a robotic swarm

S Zhong, Y Qi, Z Chen, J Wu, H Chen… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
To execute collaborative tasks in unknown environments, a robotic swarm must establish a
global reference frame and locate itself in a shared understanding of the environment …

Adversarial autoencoders for compact representations of 3D point clouds

M Zamorski, M Zięba, P Klukowski, R Nowak… - Computer Vision and …, 2020 - Elsevier
Deep generative architectures provide a way to model not only images but also complex, 3-
dimensional objects, such as point clouds. In this work, we present a novel method to obtain …

A novel binary shape context for 3D local surface description

Z Dong, B Yang, Y Liu, F Liang, B Li, Y Zang - ISPRS Journal of …, 2017 - Elsevier
Abstract 3D local surface description is now at the core of many computer vision
technologies, such as 3D object recognition, intelligent driving, and 3D model …

[PDF][PDF] Visual saliency and quality evaluation for 3D point clouds and meshes: An overview

W Lin, S Lee - APSIPA Transactions on Signal and …, 2022 - nowpublishers.com
ABSTRACT Three-dimensional (3D) point clouds (PCs) and meshes have increasingly
become available and indispensable for diversified applications in work and life. In addition …

Local voxelized structure for 3D binary feature representation and robust registration of point clouds from low-cost sensors

S Quan, J Ma, F Hu, B Fang, T Ma - Information Sciences, 2018 - Elsevier
Local feature-based 3D point cloud registration is a central issue in the fields of 3D computer
vision and robotics, and most previously proposed 3D local features are real-valued. In this …

3D point cloud descriptors: state-of-the-art

XF Han, ZA Feng, SJ Sun, GQ **ao - Artificial Intelligence Review, 2023 - Springer
The development of inexpensive 3D data acquisition devices has promisingly facilitated the
wide availability and popularity of point clouds, which attracts increasing attention to the …

Link3d: Linear keypoints representation for 3d lidar point cloud

Y Cui, Y Zhang, J Dong, H Sun… - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
Feature extraction and matching are the basic parts of many robotic vision tasks, such as 2D
or 3D object detection, recognition, and registration. As is known, 2D feature extraction and …

Enabling flexibility in manufacturing by integrating shopfloor and process perception for mobile robot workers

AC Bavelos, N Kousi, C Gkournelos, K Lotsaris… - Applied Sciences, 2021 - mdpi.com
Robotic flexibility in industry is becoming more and more relevant nowadays, especially with
the rise of the Industry 4.0 concept. This paper presents a smart execution control framework …

KDD: A kernel density based descriptor for 3D point clouds

Y Zhang, C Li, B Guo, C Guo, S Zhang - Pattern Recognition, 2021 - Elsevier
Abstract 3D feature description is one of the central techniques that rely on point clouds
since a lot of point cloud processing techniques apply the point-to-point correspondences …