Object recognition, segmentation, and classification of mobile laser scanning point clouds: A state of the art review

E Che, J Jung, MJ Olsen - Sensors, 2019 - mdpi.com
Mobile Laser Scanning (MLS) is a versatile remote sensing technology based on Light
Detection and Ranging (lidar) technology that has been utilized for a wide range of …

The benefits of very low earth orbit for earth observation missions

NH Crisp, PCE Roberts, S Livadiotti, VTA Oiko… - Progress in Aerospace …, 2020 - Elsevier
Very low Earth orbits (VLEO), typically classified as orbits below approximately 450 km in
altitude, have the potential to provide significant benefits to spacecraft over those that …

Lidar snowfall simulation for robust 3d object detection

M Hahner, C Sakaridis, M Bijelic… - Proceedings of the …, 2022 - openaccess.thecvf.com
Abstract 3D object detection is a central task for applications such as autonomous driving, in
which the system needs to localize and classify surrounding traffic agents, even in the …

Intensity scan context: Coding intensity and geometry relations for loop closure detection

H Wang, C Wang, L Xie - 2020 IEEE International Conference …, 2020 - ieeexplore.ieee.org
Loop closure detection is an essential and challenging problem in simultaneous localization
and mapping (SLAM). It is often tackled with light detection and ranging (LiDAR) sensor due …

Birdnet: a 3d object detection framework from lidar information

J Beltrán, C Guindel, FM Moreno… - 2018 21st …, 2018 - ieeexplore.ieee.org
Understanding driving situations regardless the conditions of the traffic scene is a
cornerstone on the path towards autonomous vehicles; however, despite common sensor …

Lidarsim: Realistic lidar simulation by leveraging the real world

S Manivasagam, S Wang, K Wong… - Proceedings of the …, 2020 - openaccess.thecvf.com
We tackle the problem of producing realistic simulations of LiDAR point clouds, the sensor of
preference for most self-driving vehicles. We argue that, by leveraging real data, we can …

[图书][B] LiDAR remote sensing and applications

P Dong, Q Chen - 2017 - taylorfrancis.com
Ideal for both undergraduate and graduate students in the fields of geography, forestry,
ecology, geographic information science, remote sensing, and photogrammetric …

Evaluation of sampling and cross-validation tuning strategies for regional-scale machine learning classification

C A. Ramezan, T A. Warner, A E. Maxwell - Remote Sensing, 2019 - mdpi.com
High spatial resolution (1–5 m) remotely sensed datasets are increasingly being used to
map land covers over large geographic areas using supervised machine learning …

From the semantic point cloud to heritage-building information modeling: A semiautomatic approach exploiting machine learning

V Croce, G Caroti, L De Luca, K Jacquot, A Piemonte… - Remote Sensing, 2021 - mdpi.com
This work presents a semi-automatic approach to the 3D reconstruction of Heritage-Building
Information Models from point clouds based on machine learning techniques. The use of …

A benchmark for lidar sensors in fog: Is detection breaking down?

M Bijelic, T Gruber, W Ritter - 2018 IEEE intelligent vehicles …, 2018 - ieeexplore.ieee.org
Autonomous driving at level five does not only means self-driving in the sunshine. Adverse
weather is especially critical because fog, rain, and snow degrade the perception of the …