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On the Visibility of Point Clouds
2015 IEEE International Conference on Computer Vision (ICCV), 2015Is it possible to determine the visible subset of points directly from a given point cloud? Interestingly, in [7] it was shown that this is indeed the case - despite the fact that points cannot occlude each other, this task can be performed without surface reconstruction or normal estimation. The operator is very simple - it first transforms the points
Sagi Katz, Ayellet Tal
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Proceedings of the 26th International Conference on Scientific and Statistical Database Management, 2014
We introduce the concept of the point cloud database, a new kind of database system aimed primarily towards scientific applications. Many scientific observations, experiments, feature extraction algorithms and large-scale simulations produce enormous amounts of data that are better represented as sparse (but often highly-clustered) points in a k ...
László Dobos 0001 +4 more
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We introduce the concept of the point cloud database, a new kind of database system aimed primarily towards scientific applications. Many scientific observations, experiments, feature extraction algorithms and large-scale simulations produce enormous amounts of data that are better represented as sparse (but often highly-clustered) points in a k ...
László Dobos 0001 +4 more
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Harmonic Extension on The Point Cloud
Multiscale Modeling & Simulation, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zuoqiang Shi +2 more
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Nomadic point cloud calibration
2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2014We introduce a mobile device for visual calibration of a large amount of high resolution digital images to support point cloud generation. This external nomadic device provides additional calibration information to be fed into standard 3D scene reconstruction software.
Heckes, Jürgen +4 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Fuzzy objects composed of hair, fur, or feather are impossible to scan even with the latest active or passive 3D scanners. We present a novel and practical neural rendering (NR) technique called neural opacity point cloud (NOPC) to allow high quality rendering of such fuzzy objects at any viewpoint.
Cen Wang +5 more
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Fuzzy objects composed of hair, fur, or feather are impossible to scan even with the latest active or passive 3D scanners. We present a novel and practical neural rendering (NR) technique called neural opacity point cloud (NOPC) to allow high quality rendering of such fuzzy objects at any viewpoint.
Cen Wang +5 more
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Bayesian Point Cloud Reconstruction
Computer Graphics Forum, 2006Abstract In this paper, we propose a novel surface reconstruction technique based on Bayesian statistics: The measurement process as well as prior assumptions on the measured objects are modeled as probability distributions and Bayes’ rule is used to infer a reconstruction of maximum probability.
Philipp Jenke +4 more
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Saliency Maps for Point Clouds
2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), 2020Algorithms for creating saliency maps are well established for images, even though there is no literature on such methods for point clouds. We use orthographic projections in 2D planes which are subject to well established saliency detection algorithms to create a 3D saliency map.
Victor F. Figueiredo +3 more
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Prediction of Cloud Points of Biodiesel
Energy & Fuels, 2007The predictive UNIQUAC model, previously applied with success to the description of wax formation in fossil fuels, is extended here to the modeling of the precipitation of saturated and unsaturated fatty acid methyl/ethyl esters. Correlations for the thermophysical properties of the fatty acid esters are proposed, and the model is evaluated against ...
Lopes, J. +7 more
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2003
Laser scans of real objects produce data sets (point clouds) which may have holes, due to problems with visibility or with the optical properties of the surface. We describe a method for detecting and filling these holes. After detecting the boundary of the hole, we fit an algebraic surface patch to the neighbourhood and sample auxiliary points.
Pavel Chalmovianský, Bert Jüttler
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Laser scans of real objects produce data sets (point clouds) which may have holes, due to problems with visibility or with the optical properties of the surface. We describe a method for detecting and filling these holes. After detecting the boundary of the hole, we fit an algebraic surface patch to the neighbourhood and sample auxiliary points.
Pavel Chalmovianský, Bert Jüttler
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Semantic Point Cloud Upsampling
IEEE Transactions on Multimedia, 2023Zhuangzi Li +4 more
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