Results 31 to 40 of about 140,274 (260)
DPDist: Comparing Point Clouds Using Deep Point Cloud Distance [PDF]
, 2020 We introduce a new deep learning method for point cloud comparison. Our approach, named Deep Point Cloud Distance (DPDist), measures the distance between the points in one cloud and the estimated surface from which the other point cloud is sampled. The surface is estimated locally and efficiently using the 3D modified Fisher vector representation.
Dahlia Urbach +2 more
openaire +2 more sources
Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion
Remote Sensing, 2022 The point cloud data from actual measurements are often sparse and incomplete, making it difficult to apply them directly to visual processing and 3D reconstruction.
Ruidong Hao +6 more
doaj +1 more source
Predictive point-cloud compression [PDF]
ACM SIGGRAPH 2005 Sketches on - SIGGRAPH '05, 2005 Point clouds have recently become a popular alternative to polygonal meshes for representing three-dimensional geometric models. 3D photography and scanning systems acquire the geometry and appearance of real-world objects in form of point samples.
Gumhold, S. +3 more
openaire +3 more sources
VIPDA: A Visually Driven Point Cloud Denoising Algorithm Based on Anisotropic Point Cloud Filtering
Frontiers in Signal Processing, 2022 Point clouds (PCs) provide fundamental tools for digital representation of 3D surfaces, which have a growing interest in recent applications, such as e-health or autonomous means of transport.
Tiziana Cattai +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
Remote Sensing, 2020 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 optimization method based on the grasshopper
Jian Chen +4 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
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
Colored Point Cloud Completion for a Head Using Adversarial Rendered Image Loss
Journal of Imaging, 2022 Recent advances in depth measurement and its utilization have made point cloud processing more critical. Additionally, the human head is essential for communication, and its three-dimensional data are expected to be utilized in this regard.
Yuki Ishida +2 more
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