Results 21 to 30 of about 18,303 (165)
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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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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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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Geometric 3D point cloud compression [PDF]
Pattern Recognition Letters, 2014 This work has been supported by the Spanish Government DPI2013-40534-R grant.
Vicente Morell +3 more
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Transformers in 3D Point Clouds: A Survey
CoRR, 2022 Transformers have been at the heart of the Natural Language Processing (NLP) and Computer Vision (CV) revolutions. The significant success in NLP and CV inspired exploring the use of Transformers in point cloud processing. However, how do Transformers cope with the irregularity and unordered nature of point clouds?
Lu, Dening +5 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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Learning Multiview 3D Point Cloud Registration [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 CVPR2020 - Camera ...
Zan Gojcic +4 more
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Leaves Segmentation in 3D Point Cloud [PDF]
, 2017 This paper presents a 3D plant segmentation method with an emphasis on segmentation of the leaves. This method is part of a 3D plant phenotyping project with a main objective that deals with the development of the leaf area over time. First, a 3D point cloud of a plant is obtained with Structure from Motion technique and the cloud is then segmented ...
Gélard, William +6 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.
Chong Xiang 0001 +2 more
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