Filters








4,093 Hits in 4.6 sec

A Fast Spatial Clustering Method for Sparse LiDAR Point Clouds Using GPU Programming

Yifei Tian, Wei Song, Long Chen, Yunsick Sung, Jeonghoon Kwak, Su Sun
2020 Sensors  
For real-time 3D point cloud clustering, ER-CCL is accelerated by running it in parallel with the aid of GPU programming technology.  ...  Because point clouds sensed by light detection and ranging (LiDAR) sensors are sparse and unstructured, traditional obstacle clustering on raw point clouds are inaccurate and time consuming.  ...  the computational efficiency of connected cell clustering for obstacle clustering in the driving awareness systems for unmanned vehicles, which overcame dispersed and non-sequence issue of LiDAR point  ... 
doi:10.3390/s20082309 pmid:32325631 pmcid:PMC7219594 fatcat:k7tvl4wv65brdk5afivpv7ta2e

A novel outdoor scene-understanding framework for unmanned ground vehicles with 3D laser scanners

Yan Zhuang, Guojian He, Huosheng Hu, Zhenwei Wu
2014 Transactions of the Institute of Measurement and Control  
A 2D bearing angle (BA) image is deployed to perform scene understanding so that the computational burden in the process of segmentation and classification of the 3D laser point cloud can be reduced.  ...  Outdoor scene understanding plays a key role for unmanned ground vehicles (UGVs) to navigate in complex urban environments.  ...  Acknowledgements The authors would also like to thank Mr Yungeun Choe and Professor Myung Jin Chung at Korea Advanced Institute of Science and Technology for providing the 3D point cloud dataset KAIST.  ... 
doi:10.1177/0142331214541140 fatcat:sqxdu7vzdjecpptyqirjaz5wxm

Stereo Vision for Unmanned Aerial VehicleDetection, Tracking, and Motion Control [article]

Maria N. Brunet, Guilherme Aramizo Ribeiro, Nina Mahmoudian, Mo Rastgaar
2020 arXiv   pre-print
The system consists of two parts: object detection using a stereo camera to generate 3D point cloud data and video tracking applying a Kalman filter for UAV motion modeling.  ...  An innovative method of detecting Unmanned Aerial Vehicles (UAVs) is presented.  ...  UAV Detection using Point Cloud Clustering A Euclidean clustering algorithm identifies clusters of points after the point cloud is filtered.  ... 
arXiv:2005.04183v1 fatcat:o6nuybgly5f6llwwu5dvogqsoi

Measuring Building Height Using Point Cloud Data Derived from Unmanned Aerial System Imagery in an Undergraduate Geospatial Science Course

David Kulhavy, I-Kuai Hung, Daniel R. Unger, Reid Viegut, Yanli Zhang
2021 Higher Education Studies  
The use of Unmanned Aerial Systems (UAS), also known as drones is increasing in geospatial science curricula within the United States.  ...  The independence of the students completing the project with UAS data for LP360 and ArcScene estimations, and utilizing Pictometry as an on-onscreen measuring tool, point to the need to integrate remote  ...  Acknowledgements This work was supported by a McIntire-Stennis grant administered by the Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State University, Nacogdoches, Texas, USA.  ... 
doi:10.5539/hes.v11n1p105 fatcat:b3agq44r3bcd3oqpvvx5u2rmra

Image–Based Modelling Restitution: Pipeline for Accuracy Optimisation [chapter]

Marco Limongiello, Lucas Matias Gujski
2021 Representation Challenges. Augmented Reality and Artificial Intelligence in Cultural Heritage and Innovative Design Domain  
In the case study, it has been observed that the parameter that most influences the noise in the photogrammetric point clouds is the intersection angle.  ...  The paper presents an innovative approach to support survey methods by applying AI algorithms to improve the accuracy of point clouds generated from UAV imagery.  ...  It was also considered to take into account the density of the point cloud: high distances do not allow high GSDs, and therefore not very dense point clouds and cloud sections.  ... 
doi:10.3280/oa-686.31 fatcat:kfpekwh7zngydbbtj5xi452hxe

3D Registration and Integrated Segmentation Framework for Heterogeneous Unmanned Robotic Systems

Haris Balta, Jasmin Velagic, Halil Beglerovic, Geert De Cubber, Bruno Siciliano
2020 Remote Sensing  
For this purpose, we have proposed a system for integrated multi-sensor based segmentation of 3D point clouds.  ...  In order to improve and speed up the process of outliers removal for large-scale outdoor environments, we introduced the Fast Cluster Statistical Outlier Removal (FCSOR) method.  ...  Acknowledgments: The authors specifically want to thank the institutional support of the Royal Military Academy of Belgium and Belgium Ministry of Defense for the necessary support and infrastructure in  ... 
doi:10.3390/rs12101608 fatcat:j4ipi2vxmfeprg6d4seqam5x7y

Tree Extraction of Airborne LiDAR Data Based on Coordinates of Deep Learning Object Detection from Orthophoto over Complex Mangrove Forest

Alvin Sarraga Alon
2020 International Journal of Emerging Trends in Engineering Research  
Knowing rainforest environments is rendered challenging by distance, vegetation intensity, and coverage; however, knowing the complexity and sustainability of these landscapes is important for ecologists  ...  Throughout this research, a demonstration of a new tree extraction framework inside LiDAR Point Cloud by incorporating a new tree extraction method using the bounding-box coordinates provided by deep learning-based  ...  ACKNOWLEDGEMENT The researchers would like to convey their appreciation to the following: Commission on Higher Education (CHED) DARE TO Research Grant; MR-SUAVE Project (Mangrove Remote-Sensing Unmanned  ... 
doi:10.30534/ijeter/2020/103852020 fatcat:o2kgzgkkzzgz7akxshsc5slciy

Infrastructure Mapping in Well-Structured Environments Using MAV [chapter]

Yuantao Fan, Maytheewat Aramrattana, Saeed Gholami Shahbandi, Hassan Mashad Nemati, Björn Åstrand
2016 Lecture Notes in Computer Science  
In this paper, we present a design of a surveying system for warehouse environment using low cost quadcopter. The system focus on mapping the infrastructure of surveyed environment.  ...  The map are generated based on fusing the outputs of two different methods, point cloud of corner features from Parallel Tracking and Mapping (PTAM) algorithm with estimated pillar position from a multi-stage  ...  , pillar pos); end for All pillar cloud cluster in pillar cloud do pillar f iltered pos [i] = pillar cloud cluster[i] .average(); end Function Filter(point, pillar pos) for All pos in pillar pos do if  ... 
doi:10.1007/978-3-319-40379-3_12 fatcat:4dtceoodgjhnrdxeotzahgtkca

UAV-Borne LiDAR Crop Point Cloud Enhancement Using Grasshopper Optimization and Point Cloud Up-Sampling Network

Jian Chen, Zichao Zhang, Kai Zhang, Shubo Wang, Yu Han
2020 Remote Sensing  
After the clustering segment, the pre-trained Point Cloud Up-Sampling Network (PU-net) was used for density enhancement of point cloud data and to carry out three-dimensional reconstruction.  ...  Because of low accuracy and density of crop point clouds obtained by the Unmanned Aerial Vehicle (UAV)-borne Light Detection and Ranging (LiDAR) scanning system of UAV, an integrated navigation and positioning  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs12193208 fatcat:cnhijfk6hzalblnkgqw4mrfh5y

Research Status and Prospects on Plant Canopy Structure Measurement Using Visual Sensors Based on Three-Dimensional Reconstruction

Jizhang Wang, Yun Zhang, Rongrong Gu
2020 Agriculture  
In the current research phase on 3D structural plant canopy measurement techniques, the leading algorithms of every step for plant canopy structure measurement based on 3D reconstruction are introduced  ...  Three-dimensional (3D) plant canopy structure analysis is an important part of plant phenotype studies.  ...  On the other hand, the metric scaling factor was derived through the known value of a geometrical feature in the point cloud for small-scale plant measurement without unmanned aerial systems (UAS), and  ... 
doi:10.3390/agriculture10100462 fatcat:qwl3yzuxurdahlxrv6yz72zdhi

A Precise and Robust Segmentation-Based Lidar Localization System for Automated Urban Driving

Hang Liu, Qin Ye, Hairui Wang, Liang Chen, Jian Yang
2019 Remote Sensing  
Real-time and high-precision localization information is vital for many modules of unmanned vehicles.  ...  Next, we matched the adjacent frames in Lidar odometry module and matched the current frame with the dynamically loaded pre-build feature point cloud map in Lidar localization module based on the extracted  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs11111348 fatcat:7serdxcivbgetplogo5lludb2i

Leveraging Stereo-Camera Data for Real-Time Dynamic Obstacle Detection and Tracking [article]

Thomas Eppenberger, Gianluca Cesari, Marcin Dymczyk, Roland Siegwart, Renaud Dubé
2020 arXiv   pre-print
In this paper we present a system for accurate and reliable detection and tracking of dynamic objects using noisy point cloud data generated by stereo cameras.  ...  On our test-dataset, we reach a MOTP of 0.07 ± 0.07m, and a MOTA of 85.3% for the detection and tracking of dynamic objects. We reach a precision of 96.9% for the detection of static objects.  ...  Please refer to MADNet [53] for in-depth analysis of the performance of this network. 2) Completeness: The histogram of the normalized distribution of the distances d is shown in Figure 7 .  ... 
arXiv:2007.10743v1 fatcat:vm3hplbhfjdfzele45yvtuj3w4

POINT CLOUD REGISTRATION AND ACCURACY FOR 3D MODELLING - A REVIEW

Ahmad Firdaus Razali, Mohd Farid Mohd Ariff, Zulkepli Majid
2021 Journal of Information System and Technology Management  
The point cloud is one of the data types that is used for measurement and visualisation of Earth features mapping.  ...  Experimental analysis conducted in the previous study shows an impressive result on laser scanned point cloud with very mínimum errors compared to photogrammetric point cloud.  ...  Acknowledgement The authors highly acknowledge to Universiti Teknologi Malaysia for supporting this study under research grant Vot No. 21H09, 05G12  ... 
doi:10.35631/jistm.624014 fatcat:6an6ppflxra7hm25ovhy5oanje

Canopy Roughness: A New Phenotypic Trait to Estimate Aboveground Biomass from Unmanned Aerial System

Monica Herrero-Huerta, Alexander Bucksch, Eetu Puttonen, Katy M. Rainey
2020 Plant Phenomics  
Recent developments in high-resolution imaging sensors for UAS (unmanned aerial systems) focused on collecting detailed phenotypic measurements are a potential solution.  ...  A novel pipeline for feature extraction was developed to compute canopy roughness from point clouds.  ...  As a result, point clouds are accurately georeferenced to the earth reference system World Geodetic System 84, specifying the error in this process.  ... 
doi:10.34133/2020/6735967 pmid:33575668 pmcid:PMC7869937 fatcat:aaywfmecrffc5ocdtpxeqblyhi

Automatic Clearance Anomaly Detection for Transmission Line Corridors Utilizing UAV-Borne LIDAR Data

Chi Chen, Bisheng Yang, Shuang Song, Xiangyang Peng, Ronggang Huang
2018 Remote Sensing  
is decimeter level for the LiDAR point clouds collected by our UAV inspection system.  ...  Multiple LiDAR point clouds datasets collected by a large-scale UAV power line inspection system were used to validate the effectiveness and accuracy of the proposed method.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs10040613 fatcat:nauenvrntvgjran4dxyf6w3aea
« Previous Showing results 1 — 15 out of 4,093 results