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Inverse Problems in Science and Engineering, 2011
A method based on point cloud smoothing approaches for detecting noise and outliers is introduced. This method firstly estimates thresholds according to points’ shifts after smoothing, secondly identifies outliers and noise whose shifts are more than the thresholds and lastly removes them and repeats the whole process.
Mingyue Ding, Wenguang Hou, Taiwai Chan
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A method based on point cloud smoothing approaches for detecting noise and outliers is introduced. This method firstly estimates thresholds according to points’ shifts after smoothing, secondly identifies outliers and noise whose shifts are more than the thresholds and lastly removes them and repeats the whole process.
Mingyue Ding, Wenguang Hou, Taiwai Chan
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Point clouds and Hydroinformatics
2022<p>Point cloud is made up of a multitude of three-dimensional (3D) points with one or more attributes attached. Point cloud is the third data paradigm in addition to the well-established object (vector) and gridded (raster) representations, since point cloud data can be directly collected, computed, stored, and analyzed without converting
Vitali Diaz +7 more
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Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing, 2004
Point clouds are one of the most primitive and fundamental surface representations. A popular source of point clouds are three dimensional shape acquisition devices such as laser range scanners. Another important field where point clouds are found is in the representation of high-dimensional manifolds by samples. With the increasing popularity and very
Guillermo Sapiro, Facundo Mémoli
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Point clouds are one of the most primitive and fundamental surface representations. A popular source of point clouds are three dimensional shape acquisition devices such as laser range scanners. Another important field where point clouds are found is in the representation of high-dimensional manifolds by samples. With the increasing popularity and very
Guillermo Sapiro, Facundo Mémoli
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Application of Improved Point Cloud Streamlining Algorithm in Point Cloud Registration [PDF]
2020 Chinese Control And Decision Conference (CCDC), 2020 Collect point cloud data of objects with commonly used 3D scanning equipment, the resulting point cloud data is huge. Traditional point cloud registration algorithms cannot guarantee both efficiency and accuracy. To this end, combining octree-based K-means clustering point cloud streamlining algorithm with an ICP algorithm with improved weight ratio ...
Guo Xifeng +3 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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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 +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 +4 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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2017
Phase separation of a surfactant-loaded solution happens beyond a certain critical thermodynamic state (known as the cloud point), separating the hydrophobic-rich phase in a nonpolar microenvironment from the aqueous supernatant. The dye molecules are bounded to the surfactant and subsequently separated by changing the environmental factor (temperature
Sirshendu De +2 more
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Phase separation of a surfactant-loaded solution happens beyond a certain critical thermodynamic state (known as the cloud point), separating the hydrophobic-rich phase in a nonpolar microenvironment from the aqueous supernatant. The dye molecules are bounded to the surfactant and subsequently separated by changing the environmental factor (temperature
Sirshendu De +2 more
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Compression of Plenoptic Point Clouds
IEEE Transactions on Image Processing, 2019Point clouds have been recently used in applications involving real-time capture and rendering of 3D objects. In a point cloud, for practical reasons, each point or voxel is usually associated with one single color along with other attributes. The region-adaptive hierarchical transform (RAHT) coder has been proposed for single-color point clouds.
Gustavo Sandri +2 more
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Nucleation theory and the cloud-point
Surface Science Letters, 1986On the basis of a recent proposal for the droplet distribution in the lattice-gas model, we evaluate completion times and scaled supersaturations which are consistent with existing observations in cloud-point experiments near the critical temperature. Some general concepts in nucleation theory are also reviewed.
Joaquín Marro, R. Toral
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