Results 21 to 30 of about 165,702 (282)
A digital hologram-based encryption and compression method for 3D models
Frontiers in Physics, 2022 This study proposes a novel method to compress and decompress the 3D models for safe transmission and storage. The 3D models are first extracted to become 3D point clouds, which would be classified by the K-means algorithm.
Yukai Sun +7 more
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3D CHANGE DETECTION OF POINT CLOUDS BASED ON DENSITY ADAPTIVE LOCAL EUCLIDEAN DISTANCE [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 With the development of sensors and multi-view stereo matching technology, image-based dense matching point cloud data shares higher geometric accuracy and richer spectral information, and such data is therefore widely used in change detection-related ...
J. X. Chai, Y. S. Zhang, Z. Yang, J. Wu
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DeepLabV3-Refiner-Based Semantic Segmentation Model for Dense 3D Point Clouds
Remote Sensing, 2021 Three-dimensional virtual environments can be configured as test environments of autonomous things, and remote sensing by 3D point clouds collected by light detection and range (LiDAR) can be used to detect virtual human objects by segmenting collected ...
Jeonghoon Kwak, Yunsick Sung
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SURFACE OR SKELETON? AUTOMATIC HIERARCHICAL CLUSTERING OF 3D POINT CLOUDS OF BRONZE FROG DRUMS FOR HERITAGE DIGITAL TWINS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 In the era of digital twins, high-definition 3D point clouds of cultural relics, such as the bronze drums of ancient Southeast Asia and China, are increasingly available as digital heritage.
F. Xue, W. Zhang, G. Xu, Q. Zhou, Y. Wu
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CLASSIFICATION OF AERIAL POINT CLOUDS WITH DEEP LEARNING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Due to their usefulness in various implementations, such as energy evaluation, visibility analysis, emergency response, 3D cadastre, urban planning, change detection, navigation, etc., 3D city models have gained importance over the last decades.
E. Özdemir, E. Özdemir, F. Remondino
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Equivariant Point Network for 3D Point Cloud Analysis [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Features that are equivariant to a larger group of symmetries have been shown to be more discriminative and powerful in recent studies [4], [40], [5]. However, higher-order equivariant features often come with an exponentially-growing computational cost. Furthermore, it remains relatively less explored how rotation-equivariant features can be leveraged
Haiwei Chen +4 more
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SEMANTIC ENRICHMENT OF 3D POINT CLOUDS USING 2D IMAGE SEGMENTATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 3D point cloud segmentation is computationally intensive due to the lack of inherent structural information and the unstructured nature of the point cloud data, which hinders the identification and connection of neighboring points.
A. Rai +3 more
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Generating 3D Adversarial Point Clouds [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Deep neural networks are known to be vulnerable to adversarial examples which are carefully crafted instances to cause the models to make wrong predictions. While adversarial examples for 2D images and CNNs have been extensively studied, less attention has been paid to 3D data such as point clouds.
Xiang, Chong, Qi, Charles R., Li, Bo
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EXPLORING THE POTENTIALS OF UAV PHOTOGRAMMETRIC POINT CLOUDS IN FAÇADE DETECTION AND 3D RECONSTRUCTION OF BUILDINGS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 The use of Airborne Laser Scanner (ALS) point clouds has dominated 3D buildings reconstruction research, thus giving photogrammetric point clouds less attention.
K. K. Mwangangi +3 more
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Deep Magnification-Flexible Upsampling Over 3D Point Clouds [PDF]
IEEE Transactions on Image Processing, 2021 15 pages, 16 figures, 6 ...
Yue Qian, Junhui Hou, Sam Kwong, Ying He
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