Results 31 to 40 of about 5,267,329 (301)
Discover 3D Point Cloud Processing with Python [PDF]
, 2020 Tutorial to simply set up your python environment, start processing and visualize 3D point cloud data.
Poux, Florent
core
Extraction of Interior and Exterior IFC Building Surfaces by Visibility-Based Mapping for Point-Cloud-to-BIM Comparison [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesThis work presents an element-consistent method for extracting interior and exterior surfaces from Industry Foundation Classes (IFC) building models. The approach addresses the geometric and semantic mismatch between terrestrial laser scans representing ...
R. Gesler +3 more
doaj +1 more source
Classification of ALS Point Cloud with Improved Point Cloud Segmentation and Random Forests
Remote Sensing, 2017 This paper presents an automated and effective framework for classifying airborne laser scanning (ALS) point clouds. The framework is composed of four stages: (i) step-wise point cloud segmentation, (ii) feature extraction, (iii) Random Forests (RF ...
Huan Ni, Xiangguo Lin, Jixian Zhang
doaj +1 more source
, 2018 Example Outcrop Point Cloud for Estimating Historical Shear ...
Xin Wang (5597843)
core +1 more source
RE-PU: A Self-Supervised Arbitrary-Scale Point Cloud Upsampling Method Based on Reconstruction
Applied SciencesThe point clouds obtained directly from three-dimensional scanning devices are often sparse and noisy. Therefore, point cloud upsampling plays an increasingly crucial role in fields such as point cloud reconstruction and rendering.
Yazhen Han +3 more
doaj +1 more source
Fused Projection-Based Point Cloud Segmentation
Sensors, 2022 Semantic segmentation is used to enable a computer to understand its surrounding environment. In image processing, images are partitioned into segments for this purpose.
Maximilian Kellner +2 more
doaj +1 more source
IEEE Communications MagazineAcquisition and processing of point clouds (PCs) is a crucial enabler for many emerging applications reliant on 3D spatial data, such as robot navigation, autonomous vehicles, and augmented reality. In most scenarios, PCs acquired by remote sensors must be transmitted to an edge server for fusion, segmentation, or inference.
Yulin Shao +5 more
openaire +2 more sources
Deep Learning Point Cloud Odometry
U.Porto Journal of Engineering, 2021 Achieving persistent and reliable autonomy for mobile robots in challenging field mission scenarios is a long-time quest for the Robotics research community. Deep learning-based LIDAR odometry is attracting increasing research interest as a technological
Bernardo Teixeira, Hugo Silva
doaj +1 more source
Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment
Molecular Oncology, EarlyView.This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley +1 more source
Adaptive Clustering for Point Cloud
SensorsThe point cloud segmentation method plays an important role in practical applications, such as remote sensing, mobile robots, and 3D modeling. However, there are still some limitations to the current point cloud data segmentation method when applied to ...
Zitao Lin +6 more
doaj +1 more source