Results 21 to 30 of about 528,144 (284)
Recognizing point clouds using conditional random fields [PDF]
, 2014 Detecting objects in cluttered scenes is a necessary step for many robotic tasks and facilitates the interaction of the robot with its environment. Because of the availability of efficient 3D sensing devices as the Kinect, methods for the recognition of ...
Dellen, Babette +2 more
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CoRR, 2018 Generative Adversarial Networks (GAN) can achieve promising performance on learning complex data distributions on different types of data. In this paper, we first show a straightforward extension of existing GAN algorithm is not applicable to point clouds, because the constraint required for discriminators is undefined for set data.
Chun-Liang Li +4 more
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REFINEMENT OF COLORED MOBILE MAPPING DATA USING INTENSITY IMAGES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Mobile mapping systems (MMS) can capture dense point-clouds of urban scenes. For visualizing realistic scenes using point-clouds, RGB colors have to be added to point-clouds.
T. Yamakawa +3 more
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Remote Sensing, 2021 Estimation of urban tree canopy parameters plays a crucial role in urban forest management. Unmanned aerial vehicles (UAV) have been widely used for many applications particularly forestry mapping.
Ebadat Ghanbari Parmehr, Marco Amati
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Enriching Thermal Point Clouds of Buildings using Semantic 3D building Models [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesThermal point clouds integrate thermal radiation and laser point clouds effectively. However, the semantic information for the interpretation of building thermal point clouds can hardly be precisely inferred. Transferring the semantics encapsulated in 3D
J. Zhu +4 more
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Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning [PDF]
, 2019 We show that denoising of 3D point clouds can be learned unsupervised, directly from noisy 3D point cloud data only. This is achieved by extending recent ideas from learning of unsupervised image denoisers to unstructured 3D point clouds.
Hermosilla, Pedro +2 more
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idea journal, 2023 Laser scanning holds out the possibility of extreme certainty. Digital scanning has become deeply integrated in contemporary archaeological surveying, and in architectural heritage and preservation contexts digital scans are now common. Certainty in this text-based essay is understood as an affect, an experiential quality rather than an absolute ...
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Difference of Normals as a Multi-Scale Operator in Unorganized Point Clouds [PDF]
, 2012 A novel multi-scale operator for unorganized 3D point clouds is introduced. The Difference of Normals (DoN) provides a computationally efficient, multi-scale approach to processing large unorganized 3D point clouds.
, +4 more
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Applied Sciences, 2022 TLS can quickly and accurately capture object surface coordinates. However, TLS point clouds cannot cover the entire surface of the target object, due to block of view and limitation of measurement condition.
He Jia +5 more
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3D Point Cloud Recognition Based on a Multi-View Convolutional Neural Network
Sensors, 2018 The recognition of three-dimensional (3D) lidar (light detection and ranging) point clouds remains a significant issue in point cloud processing. Traditional point cloud recognition employs the 3D point clouds from the whole object.
Le Zhang, Jian Sun, Qiang Zheng
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