Results 1 to 10 of about 524,955 (164)
Point clouds segmentation of rapeseed siliques based on sparse-dense point clouds mapping
Frontiers in Plant Science, 2023 In this study, we propose a high-throughput and low-cost automatic detection method based on deep learning to replace the inefficient manual counting of rapeseed siliques.
Yuhui Qiao +14 more
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IEEE Access, 2022 Point cloud data of cracks can be used for various purposes such as crack detection, depth calculation and crack segmentation. Upsampling low-density point clouds can help to improve the performance of those tasks.
Nhung Hong Thi Nguyen +5 more
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MIXED REALITY VISUALIZATION OF POINT CLOUDS FOR SUPPORTING TERRESTRIAL LASER SCANNING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 3D point clouds from terrestrial laser scanners (TLS) are used in a variety of fields and applications. To acquire high-quality point clouds that have enough point density, small scanning errors, and no lack of points in important regions, appropriate ...
K. Ohno, H. Date, S. Kanai
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Geodesy and Geodynamics, 2022 Clustering filtering is usually a practical method for light detection and ranging (LiDAR) point clouds filtering according to their characteristic attributes.
Xingsheng Deng, Guo Tang, Qingyang Wang
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IMAGE TO POINT CLOUD TRANSLATION USING CONDITIONAL GENERATIVE ADVERSARIAL NETWORK FOR AIRBORNE LIDAR DATA [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 This study introduces a novel image to a 3D point-cloud translation method with a conditional generative adversarial network that creates a large-scale 3D point cloud.
T. Shinohara, H. Xiu, M. Matsuoka
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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.
Urbach, Dahlia +2 more
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Point Density Variations in Airborne Lidar Point Clouds
Sensors, 2023 In spite of increasing point density and accuracy, airborne lidar point clouds often exhibit point density variations. Some of these density variations indicate issues with point clouds, potentially leading to errors in derived products.
Vaclav Petras +4 more
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POINT-CLOUD COMPRESSION FOR VEHICLE-BASED MOBILE MAPPING SYSTEMS USING PORTABLE NETWORK GRAPHICS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects．Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving ...
K. Kohira, H. Masuda
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Applied Sciences, 2022 Road high-precision mobile LiDAR measurement point clouds are the digital infrastructures for high-precision maps, autonomous driving, digital twins, etc. High-precision automated semantic segmentation of road point clouds is a crucial research direction.
Peng Cheng +5 more
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INVESTIGATION OF POINTNET FOR SEMANTIC SEGMENTATION OF LARGE-SCALE OUTDOOR POINT CLOUDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 Semantic segmentation of point clouds is indispensable for 3D scene understanding. Point clouds have credibility for capturing geometry of objects including shape, size, and orientation.
A. Nurunnabi +4 more
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