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222 results for “Point cloud”
Fembøringen Merkur - Point cloud
Scanned with an iPhone 13 Pro. Source: Objaverse 1.0 / Sketchfab
AGNSW 2 Point Cloud
Source: Objaverse 1.0 / Sketchfab
Notre Dame Paris Facade - Hi Res Point Cloud
Made from 105 tourist photos from Flickr and Wikimedia. Source: Objaverse 1.0 / Sketchfab
Small Magellanic Cloud Deep Fields X-Ray Point Source Catalog
This table contains the results of a pair of 100 ks Chandra observations of the Small Magellanic Cloud (SMC) to survey high-mass X-ray binaries (HMXBs), stars, and low-mass X-ray binaries (LMXBs)/cataclysmic variables down to L<sub>X</sub> = 4.3 x 10<sup>32</sup> erg s<sup>-1</sup>. The two SMC Deep Fields (DFs) are located in the most active star-forming region of the SMC bar, with Deep Field-1 positioned at the most pulsar-rich location identified from previous surveys. Two new pulsars were discovered in outburst, CXOU J004929.7-731058 (P = 892 s) and CXOU J005252.2-721715 (P = 326 s), and three new HMXB candidates were identified. Of the 15 Be-pulsars now known in the field, 13 were detected, with pulsations seen in 9 of them. Ephemerides demonstrate that 6 of the 10 pulsars known to exhibit regular outbursts were seen outside their periastron phase, and quiescent X-ray emission at L<sub>X</sub> = 10<sup>(33-34)</sup> erg s<sup>-1</sup> is shown to be common. Comparison with ROSAT, ASCA, and XMM-Newton catalogs resulted in positive identification of several previously ambiguous sources. Bright optical counterparts exist for 40 of the X-ray sources, of which 33 are consistent with early-type stars (M<sub>V</sub> < -2, B-V < 0.2), and are the subject of a companion paper to the reference paper. The results point to an underlying HMXB population density up to double that of active systems. The full catalog of 394 point sources is presented in this table; detailed analyses of the source timing and spectral properties are available in the reference paper. The aim-points for these Chandra observations were as follows: DF1 had J2000.0 coordinates of 00 53 34.50 -72 26 43.2 and DF2 had J2000.0 coordinates of 00 50 41.40 -73 16 10.3. This table was created by the HEASARC in August 2010 based on the electronic version of Table 2 from the reference paper which was obtained from the ApJ web site. This is a service provided by NASA HEASARC .
Small Magellanic Cloud Wing Survey Chandra X-Ray Point Source Catalog
The authors have detected 523 X-ray sources in a survey of the Small Magellanic Cloud (SMC) Wing with the Chandra X-ray Observatory. By cross-correlating the X-ray data with optical and near-infrared catalogs, they have found 300 matches. Using a technique that combines X-ray colors and X-ray to optical flux ratios, they have been able to assign preliminary classifications to 265 of the objects. The identifications include 4 pulsars, 1 high-mass X-ray binary (HMXB) candidate, 34 stars and 185 active galactic nuclei (AGN). In addition, the authors have classified 32 sources as hard AGN which are likely absorbed by local gas and dust, and 9 soft AGN whose nature is still unclear. Considering the abundance of HMXBs discovered so far in the Bar of the SMC the number that have been detected in the Wing is low. Observations in the Wing of the SMC were made from 2005 July to 2006 March with Chandra. The survey consisted of 20 fields, with exposure times ranging from 8.6 - 10.3 ks. X-ray parameters for 523 sources detected in the Wing of the SMC with Chandra are presented. For each source equatorial coordinates, positional error, net counts (total counts minus background counts) in the 0.5 - 8.0 keV band, signal-to-noise of the detection and source flux in the 0.5 - 8.0 keV band are given. The median, compressed median and normalized quartile ratio of the photon energy distribution, determined using quantile analysis, are given for sources with three or more counts. For the sources that have optical counterparts the V- and R-band magnitudes, B-V color, X-ray to optical flux ratios based on the V- and R-band magnitudes, and a preliminary classification for the sources are given. This table was created by the HEASARC in June 2008 based on the <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/MNRAS/383/330">CDS Catalog J/MNRAS/383/330</a> file table2.dat. This is a service provided by NASA HEASARC .
SnowEx20 Boise State University Terrestrial Laser Scanner (TLS) Point Cloud V001
This data set contains terrestrial laser scanner (TLS) point cloud data collected as part of the 2020 SnowEx campaign in Grand Mesa, Colorado. Data were collected under both snow-off (September 2019) and snow-on (February 2020) conditions, at both open and forested locations. Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i). These TLS data can be used to determine snow depth and explore the interactions between snow and vegetation.
SnowEx20 CRREL Terrestrial Laser Scanner (TLS) Point Cloud V001
This data set contains terrestrial LIDAR survey (TLS) point cloud data collected at Grand Mesa, Colorado as part of the 2020 SnowEx campaign. Data were collected in fall 2019 (September) and winter 2020 (January and February). Each data file contains X, Y, and Z coordinates (Easting, Northing, and Elevation), along with ancillary information, such as intensity (i) and color (R,G,B), where available.
SnowEx17 CRREL Terrestrial Laser Scanner (TLS) Point Cloud V001
This data set contains terrestrial LIDAR survey (TLS) point cloud data collected at Grand Mesa, Colorado as part of the 2017 SnowEx campaign. Data were collected in the fall (September and October) and winter (February) seasons. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), along with ancillary information, such as intensity (i) and color (R,G,B), where available. This is unprocessed data which has not been classified by land use (e.g. bare earth, low vegetation, trees).
Chamaeleon I North Cloud Chandra X-Ray Point Source Catalog
This table contains the Chamaeleon (Cha) I North Cloud Chandra X-Ray point source catalog. Sensitive X-ray imaging surveys provide a new and effective tool to establish the census of pre-main-sequence (PMS) stars in nearby young stellar clusters. A deep Chandra X-Ray Observatory (CXO) observation of PMS stars in the Chamaeleon I North cloud achieved a limiting total-band X-ray luminosity of log L<sub>t</sub> ~ 10<sup>27</sup> ergs/s (0.5 - 8 keV band) in a 0.8 x 0.8 pc<sup>2</sup> region. Of the 107 X-ray sources, 37 are associated with Galactic stars, of which 27 are previously recognized cloud members. These include 3 PMS brown dwarfs: the protostellar brown dwarf ISO 192 has a particularly high level of magnetic activity. Follow-up optical photometry and spectroscopy establish that 9-10 of the Chandra sources are probably magnetically active background stars. No new X-ray-discovered stars were confidently found despite the high sensitivity of the Chandra observation. From these findings, the authors argue that the sample of 27 PMS cloud members in the Chandra field is uncontaminated and complete down to K = 12 or a stellar mass of about 0.1 solar masses. A 16'x 16' region of the Cha I North cloud was observed with the imaging array of the Advanced CCD Imaging Spectrometer (ACIS-I) detector on board the Chandra X-Ray Observatory. The observation took place on 2001 July 2.25-3.04 UT with the detector aimpoint set at 11 10 00.0, -76 35 00 (J2000.0 RA and Declination). The effective exposure was 66.3 ksec. The authors also obtained VI-band CCD images of most of the ACIS field with the 1m telescope and CCD detector at the South African Astronomical Observatory (SAAO) during 2002 February. This table was created by the HEASARC in February 2007 based on <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/ApJ/614/267">CDS catalog J/ApJ/614/267</a> files table1.dat, table2.dat and table3.dat. This is a service provided by NASA HEASARC .
SnowEx20 Boise State University Raw Terrestrial Laser Scanner (TLS) Point Cloud V001
This data set contains raw, unprocessed terrestrial laser scanner (TLS) point cloud data collected as part of the 2020 SnowEx campaign in Grand Mesa, Colorado. Data were collected under both snow-off (September 2019) and snow-on (February 2020) conditions, at both open and forested locations. Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i). A processed version of this data set can be found here: https://doi.org/10.5067/F0M99WK7JW4X.
ASO L4 Lidar Point Cloud Digital Terrain Model 3m UTM Grid V001
This data set provides 3 m gridded, bare-earth elevations (excluding trees) that are used as the baseline for the Airborne Snow Observatory (ASO) snow-on products. The data were collected during snow-free conditions as part of the NASA/JPL ASO aircraft survey campaigns.
Small Magellanic Cloud XMM-Newton Point Source Catalog
The XMM-Newton survey of the Small Magellanic Cloud (SMC) yielded complete coverage of the bar and eastern wing in the 0.2-12.0 keV energy band. In addition to the main-field (5.58 deg<sup>2</sup>), available outer fields were included in the catalogue, yielding a total field area of 6.32 deg<sup>2</sup>. This catalog comprises 3,053 unique X-ray point sources and sources with moderate extent that have been reduced from 5,236 individual detections found in 100 observations between April 2000 and April 2010 (the details of these exposures are given in Table B.1 of the reference paper). For 927 sources, there were detections at multiple epochs, with some SMC fields observed up to 36 times. The detected sources have a median position uncertainty of 1.3 arcseconds (1 sigma) and limiting fluxes down to ~1 x 10<sup>-14</sup> erg/s/cm<sup>2</sup> in the 0.2-4.5 keV band, corresponding to X-ray luminosities of ~5 x 10<sup>33</sup> erg/s for sources located in the SMC. Sources have been classified using X-ray hardness ratios, X-ray variability, and their multi-wavelength properties. In their paper, the authors discuss the statistical properties of the detected X-ray sources, like the spatial distribution, X-ray color diagrams, luminosity functions, and time variability. They have identified 49 SMC high-mass X-ray binaries (HMXB), four super-soft X-ray sources (SSS), 34 foreground stars, and 72 active galactic nuclei (AGN) behind the SMC. In addition, they found candidates for SMC HMXBs (45) and faint SSSs (8) as well as AGN (2092) and galaxy clusters (13). Notice that X-ray sources with high extent (>40 arcseconds), e.g. supernova remnants and galaxy clusters, have been previously presented by Haberl et al. (2012, A&A, 545, A128) and are not included in this table. To investigate the spectral behavior of all sources, the authors used hardness ratios HR<sub>i</sub> (i = 1, 2, 3, 4), defined by HR<sub>i</sub> = (R<sub>i+1</sub> - R<sub>i</sub>)/(R<sub>i+1</sub> + R<sub>i</sub>), where R<sub>i</sub> is the count rate in energy band i as defined by: <pre> Band Energy Range 1 0.2-0.5 keV 2 0.5-1.0 keV 3 1.0-2.0 keV 4 2.0-4.5 keV 5 4.5-12. keV </pre> To increase statistics, the authors also calculated average HR_i<sub>s</sub>, combining all available instruments and observations. HR<sub>i</sub> is not given if both rates R<sub>i</sub> and R<sub>i+1</sub> are null or if the 1-sigma uncertainty of Delta(HR<sub>i</sub>) covers the complete HR interval from -1 to +1. To convert an individual count rate R<sub>i</sub> of an energy band i into a setup-independent, observed flux F<sub>i</sub>, the authors calculated energy conversion factors (ECFs) f<sub>i</sub> = R<sub>i</sub>/F<sub>i</sub> , as described in Sect. A.3 of the reference paper. For the calculation, they assumed a universal spectrum for all sources, described by a power-law model with a photon index of 1.7 and a photo-electric foreground absorption by the Galaxy of N<sub>H,Gal</sub> = 6 x 10<sup>20</sup> cm<sup>-2</sup> (average for the SMC main field in the H I map of Dickey & Lockman 1990, ARAA, 28, 215). In addition to the fluxes for each detection, the authors calculated flux upper limits F<sub>UL</sub> for each observation and source, if the source was observed but not detected in an individual observation. As for the initial source detection, they used the emldetect task to fit sources, but kept the source positions fixed at the master positions and accepted all detection likelihoods in order to get an upper limit for the flux. This table was created by the HEASARC in October 2013 based on <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/A+A/558/A3">CDS Catalog J/A+A/558/A3</a> file smc_src.dat. This is a service provided by NASA HEASARC .
SnowEx17 Boise State University Raw Terrestrial Laser Scanner (TLS) Point Cloud V001
This data set contains raw, unprocessed terrestrial laser scanner (TLS) point cloud data collected as part of the 2017 SnowEx campaign in Grand Mesa, Colorado. Data were collected in the fall (September 2016) and winter (February 2017). Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i).
Rosette Molecular Cloud Chandra X-Ray Point Source Catalog
The authors of this study have explored the young stellar populations in the Rosette Molecular Cloud (RMC) region with high spatial resolution X-ray images from the Chandra X-ray Observatory, which are effective in locating weak-lined T Tauri stars as well as disk-bearing young stars. A total of 395 X-ray point sources are detected, 299 of which (76%) have an optical or near-infrared (NIR) counterpart identified from deep FLAMINGOS images. From X-ray and mass sensitivity limits, the authors infer a total population of ~1700 young stars in the survey region. Based on smoothed stellar surface density maps, they investigate the spatial distribution of the X-ray sources and define three distinctive structures and substructures within them. Structures B and C are associated with previously known embedded IR clusters, while structure A is a new X-ray-identified unobscured cluster. A high-mass protostar RMCX 89 = IRAS 06306+0437 and its associated sparse cluster are studied. The different subregions are not coeval but do not show a simple spatial-age pattern. Disk fractions vary between subregions and are generally <~ 20% of the total stellar population inferred from the X-ray survey. The data are consistent with speculations that triggered star formation around the H II region is present in the RMC, but do not support a simple sequential triggering process through the cloud interior. While a significant fraction of young stars are located in a distributed population throughout the RMC region, it is not clear if they originated in clustered environments. This HEASARC table contains the 348 primary sources listed in Table 1 of the reference paper, as well as the 47 tentative sources listed in Table 2 (the latter having a likelihood > 10<sup>-3</sup> of being a spurious background fluctuation based on Poisson statistics), to make a total of 395 X-ray sources. The information on optical and infrared counterparts to these X-ray sources which was provided in Table 4 of the reference paper has also been included herein. In order to allow users to clearly identify these 2 samples, the HEASARC has created a parameter source_sample which is set to 'P' for the Table 1 primary sources and to 'T' for the Table 2 tentative sources. This HEASARC table also contains the X-ray spectroscopic information derived for 158 sources which have photometric significance (the snr parameter) >= 2.0 which was presented in Table 3 of the reference paper. All spectral fits used the "wabs(apec)" model in XSPEC and assumed 0.3 * Z_Sun abundances. The quoted emission measures and X-ray luminosities assume a distance to the Rosette molecular cloud of 1.4 kpc. This table was created by the HEASARC in July 2009 based on the merger of electronic versions of tables 1, 2, 3 and 4 from the above reference which were obtained from the ApJ web site. This is a service provided by NASA HEASARC .
SnowEx17 Boise State University Terrestrial Laser Scanner (TLS) Point Cloud V001
This data set contains terrestrial laser scanner (TLS) point cloud data collected as part of the 2017 SnowEx campaign in Grand Mesa, Colorado. Data were collected under both snow-off (September 2016) and snow-on (February 2017) conditions, at both open and forested locations. Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i). These TLS data can be used to determine snow depth and explore the interactions between snow and vegetation.
Monoceros R2 Cloud Chandra X-Ray Point Source Catalog
The Monoceros R2 (Mon R2) Cloud X-Ray Point Source Catalog contains the results of the Chandra ACIS-I observation of the central region of this high-mass star-forming region (SFR), which lies at a distance of 830pc. With a deep exposure of ~ 100 ks, the authors detected 368 X-ray sources, ~80% of which were identified with near-infrared (NIR) counterparts. They systematically analyzed the spectra and time variability of most of the X-ray emitting sources and provide a comprehensive X-ray source catalog for the first time. Using the J-, H- and K-bands magnitudes of the NIR counterparts, they have estimated the evolutionary phase, classical T Tauri (CTT) stars and weak-lined T Tauri (WTT) stars, and the masses of the X-ray emitting sources, and have analyzed their X-ray properties as a function of age and mass. They found a marginal hint that CTT stars have a slightly higher temperature (2.4 keV) that of WTT stars (2.0 keV). A significant fraction of the high- and intermediate-mass sources have time variability and high plasma temperatures (2.7 keV) simailar to those of the low-mass stars (2.0 keV). This supports earlier proposals that high- and intermediate-mass young stellar objects emit X-rays via magnetic activity. The authors also found a significant difference in the spatial distribution between X-ray and NIR sources. This table was created by the HEASARC in January 2007 based on CDS table J/PASJ/55/635/table1.dat This is a service provided by NASA HEASARC .
Golden Gate Bridge - Point Cloud
Point cloud obtained from drone video Source: Objaverse 1.0 / Sketchfab
Point Cloud Curb Detection Dataset
<p>This dataset contains labeled point cloud data that was captured by a car equipped with a mobile laser scanner.</p> <p>It is part of the ICMLA publication <a href="https://ieeexplore.ieee.org/document/9680221">Large-Scale Curb Extraction Based on 3D Deep Learning and Iterative Refinement Post-Processing</a></p> <p>The dataset is supposed to serve as a benchmark for automated large-scale point cloud curb detection approaches.</p> <p> </p> <p>The dataset is derived from the publicly available KITTI360 dataset published in the paper</p> <p><a href="https://ps.is.tuebingen.mpg.de/publications/xie2016cvpr">Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer</a> by Jun Xie et al.</p> <p><br> LICENSE</p> <p><a href="https://creativecommons.org/licenses/by-nc-sa/3.0/">Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)</a> License</p> <p>If you find this dataset useful, please cite the following publication:</p> <pre><code>@INPROCEEDINGS{9680221, author={Schmitz, Jan-Christoph and Bauer, Adrian and Kummert, Anton}, booktitle={2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)}, title={Large-Scale Curb Extraction Based on 3D Deep Learning and Iterative Refinement Post-Processing}, year={2021}, volume={}, number={}, pages={558-563}, doi={10.1109/ICMLA52953.2021.00093}}</code></pre> <p> </p> <p>Supported by the State of North Rhine-Westphalia, Germany</p>
Point cloud data for worker safety project
<p>This three files are the scanned data for the worker safety project. The scanned location includes two urban intersections and a part of an urban highway. These three files can be opened by Autodesk Recap, which is a point cloud manipulating software. This data can be requested by contacting Dr. Semiha Ergan at semiha@nyu.edu</p>
Point Cloud (Dept. Of Engineering)
<p>These are the registered and aligned point clouds from the Engineering Department acquired by the CIT lab. There are the second floor and part of the third floor of east wing of the Baker Building and the second floor of the central wing.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.