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278 results for “STEREO”
DEM generated from ASTER L1A v.3 stereo imagery acquired over Mt. Rainier on July 31st, 2017 using Ames Stereo Pipeline
<p>This DEM was generated using ASTER L1A dataset was procured from <a href="https://www.earthdata.nasa.gov/">NASA EarthData portal</a> through the stereo processing example in <a href="https://github.com/uw-cryo/asp_tutorials/tree/master">asp_tutorials</a>.</p><ul><li>We intend to use this DEM during the co-registration tutorial.</li></ul><p> </p>
Polonez stereo DSS-361 UNITRA DIORA
Polonez stereo DSS-361 UNITRA DIORA Muzeum Miejskie Dzierżoniów Diora 3D Source: Objaverse 1.0 / Sketchfab
Idealized wave data in support of Directional Breaking Kinematics Observations from 3D Stereo Reconstruction of Ocean Waves
<p>You will find the WaveWatchIII data output from idealized solutions of Romero 2019, ST4 and ST6</p> <p>Data are in Netcdf format and include metadata.</p> <p>Each file corresponds to a duration-limited solution with constant wind speed of 13 m/s</p>
Mesoscale stereo retrievals from Hunga Tonga-Hunga Ha'apai Eruption of 15 January 2022
<p>Stereo methods using GOES-17 and Himawari-8 applied to the Hunga Tonga-Hunga Ha'apai volcanic plume on 15 January 2022 show overshooting tops reaching 50-55 km altitude, a record in the satellite era. Plume height is important to understand dispersal and transport in the stratosphere and climate impacts. Stereo methods, using geostationary satellite pairs, offer the ability to accurately capture the evolution of plume top morphology quasi-continuously over long periods. Manual photogrammetry estimates plume height during the most dynamic early phase of the eruption and a fully automated algorithm retrieves both plume height and advection every 10 minutes during a more frequently sampled and stable phase beginning three hours after the eruption. Stereo heights are confirmed with Global Navigation Satellite System Radio Occultation (GNSS-RO) bending angles, showing that much of the plume was lofted 30–40 km into the atmosphere. Cold bubbles are observed in the stratosphere with brightness temperature of ~173K.</p>
Text-fig. 1. CUWM 40, palate of Diamantohyus africanus from Moghara, Egypt, stereo occlusal view. in New Suoid Fossils (Mammalia, Artiodactyla) From The Miocene Of Moghara, Egypt, And Gebel Zelten, Libya: Biochronological Implications
Text-fig. 1. CUWM 40, palate of Diamantohyus africanus from Moghara, Egypt, stereo occlusal view.
Text-fig. 18. Stereo images of fossil marine gastropod steinkerns from White Patch Fossil Site 1. in Stratigraphy, Chronology And Palaeontology Of The Tertiary Rocks Of The Cheringoma Plateau, Mozambique
Text-fig. 18. Stereo images of fossil marine gastropod steinkerns from White Patch Fossil Site 1.
SC-XRD diffraction images of stereo-defined pyrrolidine ligand
<p>Structures of a piperazine in the publication: "Direct and Stereospecific [3+2] Synthesis of Pyrrolidines from Simple Unactivated Alkenes" Angew. Chem. Int. Ed. 2017, DOI:10.1002/anie.201706682</p> <p>Structure solutions were deposited in the CCDC: 1528080<br> https://www.ccdc.cam.ac.uk/structures-beta/Search?id=doi:10.1002/anie.201706682</p>
Data from : Measuring nearshore waves at break point in 4D with Stereo-GoPro photogrammetry
<p>This dataset was collected with a stereophotogrammetric method, using a cost-effective stereo system composed of two GoProTM (Hero 7) video cameras.</p> <p>The result is a geotiff DEM time series, with a resolution of 0.2 m, focusing on close-range measurements of nearshore waves at break point.</p> <p>Data collected in the framework of the WEST project (Natural Breaking WavEs and Sediment Transport during beach recovery - ANR-20-CE01-009) granted by the Agence Nationale pour la Recherche (ANR).</p>
Plenoptic 2.0 - RayTrix R8 and RayTrix R32 - Stereo View Video Sequence: TempleBoatGiant
<p>The test sequence "Plenoptic 2.0 - RayTrix R8 and RayTrix R32 - Stereo View Video Sequence: TempleBoatGiant" is provided by Sarah Fachada, Daniele Bonatto, Jaime Sancho, Gauthier Lafruit,Mehrdad Teratani, and Eduardo Juárez, members of the LISA department, EPB (Ecole Polytechnique de Bruxelles), ULB (Université Libre de Bruxelles), Belgium and CITSEM (Centro de Investigación en Tecnologías Software y Sistemas Multimedia para la Sostenibilidad), UPM (Universidad Politecnica de Madrid), Spain.</p> <h2>License:</h2> <p>CC BY-NC-SA</p> <h2>Terms of Use:</h2> <p>Any kind of publication or report using this sequence should refer to the following references:</p> <p>[1] **Sarah Fachada, Daniele Bonatto, Jaime Sancho, Gauthier Lafruit, Mehrdad Teratani and Eduardo Juárez, "Plenoptic 2.0 - RayTrix R8 and RayTrix R32 - Stereo View Video Sequence: TempleBoatGiant," 2024.07, 10.5281/zenodo.12663777.**</p> <blockquote> <p>@misc{fachada_templeboatgiantvideo_2024,</p> <p> title = {{Plenoptic} 2.0 {Raytrix} {R8} and {Raytrix} {R32} - {Stereo} {View} {Video} {Sequence}: {TempleBoatGiant}},</p> <p> author = {Fachada, Sarah and Bonatto, Daniele and Sancho, Jaime and Lafruit, Gauthier and Teratani, Mehrdad and Juárez, Eduardo},</p> <p> month = jul,</p> <p> year = {2024},</p> <p> doi = {10.5281/zenodo.12663777}</p> <p>}</p> </blockquote> <p>[2] **Sarah Fachada, Daniele Bonatto, Jaime Sancho, Gauthier Lafruit, Mehrdad Teratani and Eduardo Juárez, "[LVC] A New Plenoptic 2.0 - RayTrix R8 and RayTrix R32 - Stereo View Video Sequence: TempleBoatGiant [M68363]," 2024.07, Sapporo, Japan, ISO/IEC JTC1/SC29/WG04**</p> <blockquote> <p>@article{fachada_lvc_templeboatgiantvideo_2024,</p> <p> title = {{[LVC]} a {New} {Plenoptic} 2.0 {Raytrix} {R8} and {Raytrix} {R32} - {Stereo} {View} {Video} {Sequence}: {TempleBoatGiant}},</p> <p> author = {Fachada, Sarah and Bonatto, Daniele and Sancho, Jaime and Lafruit, Gauthier and Teratani, Mehrdad and Juárez, Eduardo},</p> <p> month = jul,</p> <p> year = {2024},</p> <p> address = {Sapporo, Japan},</p> <p> edition = {MPEG2021/M68363},</p> <p> journal = {ISO/IEC JTC1/SC29/WG04}</p> <p>}</p> </blockquote> <h2>Production:</h2> <p>Laboratory of Image Synthesis and Analysis, LISA department, Ecole Polytechnique de Bruxelles, Université Libre de Bruxelles, Belgium,</p> <p>Centro de Investigación en Tecnologías Software y Sistemas Multimedia para la Sostenibilidad, CITSEM, Universidad Politécnica de Madrid, Spain.</p> <h2>Content:</h2> <p>This dataset contains a dynamic scene representing an artistic view of a boat floating on an ocean made of colored blocks, near a temple, while a giant is chasing them. The boat is animated by a giant wooden hand. The dataset is in the format of plenoptic images extracted from Raytrix [1] .rays files. The dataset was acquired with two Raytrix cameras, the R8 and the R32, mounted on the UPM’s robotic bench, keeping the same positon during the video. The distance transformation between the two Total Focus cameras is T= (193.968, 6.13558, 126.865) (mm), R= (-2.7386289, -11.0520427, 1.479145) (°). The main lens focal length focals are F=25 for the R8 and F=50 for the R32.</p> <p>The dataset additionally contains calibration images of a checkerboard with square size of 12mm.</p> <p>1. **Scene**</p> <ul> <li>300 frames of processed images extracted from .ray file.</li> <li>Total focus videos</li> </ul> <p>2. **Calibration images:**</p> <ul> <li>Processed and raw views of a checkerboard with 12mm square size.</li> <li>Raw gray images to extract the processed image.</li> </ul> <p>MLA Calibration files are provided in XML format.</p> <h2>The dataset contains:</h2> <p>- `video_{R32/R8}` folders containing:</p> <ul> <li>Processed plenoptic PNG files</li> <li>XML MLA calibration files</li> <li>Total focus MP4 videos extracted with RxLive software for visualization of the scene.</li> </ul> <p>- A `checkerboard` folder containing:</p> <ul> <li>XML MLA calibration files</li> <li>8 Plenoptic raw images in PNG format of a checkerboard with square size of 12mm</li> <li>8 Plenoptic processed images in PNG format of the checkerboard</li> <li>Gray images in PNG for raw file processing.</li> </ul> <h2>References and links:</h2> <p>[1] https://raytrix.de/</p> <h2>Acknowledgments:</h2> <p>Sarah Fachada is a Postdoctoral Researcher of the Fonds de la Recherche Scientifique - FNRS, Belgium.</p> <p>This work was supported in part by the HoviTron project (no. 951989), the FER 2021 project (no. 1060H000066-FAISAN), the Emile DEFAY 2021 project (no. 4R00H000236), and the FER 2023 project (no. 1060H000075).</p> <p>Additionally, this work has been funded by the project AIMS5.0, supported by the Chips Joint Undertaking and its members, including top-up funding by National Funding Authorities from involved countries (no. 101112089), and the European project STRATUM (no. 101137416). The robotic bench was funded by “Programa Propio UPM” in the call “convocatoria de ayudas a centros e institutos de I+D+i”.</p>
Mono-to-Stereo Conversion Evaluation Dataset
<p>MONO-TO-STEREO CONVERSION EVALUATION DATASET.</p> <p>This dataset has been constructed from audio excerpts taken from the Bach10 dataset by Duan et al. [1]. This database has been used to evaluate the effectiveness of a mono-to-stereo converter by means of a listening test. Results were presented in my PhD thesis [2], in Chapter 6, on pages 167-176.</p> <p>[1] Z. Duan, B. Pardo, and C. Zhang, "Multiple fundamental frequency estimation by modelling spectral peaks and non-peak regions," IEEE Transactions on Audio, Speech and Language Processing, vol. 18, no. 8, pp. 2121-2133, 2010.</p> <p>[2] Delgado Castro, A. "Iterative separation of note events from single-channel Polyphonic Recordings," Ph.D. University of York. 2019.</p>
Associated coordinate and mtz files for "Crystal structure of cytochrome P450 NysL and the structural basis for stereo- and regio- selective oxidation of antifungal macrolides"
<p>Coordinate and mtz files for the associated protein structures reported in "Crystal structure of cytochrome P450 NysL and the structural basis for stereo- and regio- selective oxidation of antifungal macrolides".</p>
Stereo-seq E12.5_E1S3 bin 200 expression matrix (dgC Matrix), spatial locations (.csv), and h5ad file (scanpy flavor)
<p>Expression matrix in rds file format and spatial locations of E12.5_E1S3 downloaded from the Mouse Organogenesis Spatiotemporal Transcriptomic Atlas. Files were processed using an adapted version of the STOMICS Analysis Workflow (SAW) pipeline. </p>
Data for: Multi-LEO satellite stereo winds
The stereo-winds method follows trackable atmospheric cloud features from multiple viewing perspectives over multiple times, generally involving multiple satellite platforms. Multi-temporal observations provide information about the wind velocity and the observed parallax between viewing perspectives provides information about the height. The stereo-winds method requires no prior assumptions about the thermal profile of the atmosphere to assign a wind height, since the height of the tracked feature is directly determined from the viewing geometry. The method is well developed for pairs of Geostationary (GEO) satellites and a GEO paired with a Low Earth Orbiting (LEO) satellite. However, neither GEO-GEO nor GEO-LEO configurations provide coverage of the poles. In this paper, we develop the stereo-winds method for multi-LEO configurations, to extend coverage from pole to pole. The most promising multi-LEO constellation studied consists of Terra/MODIS and Sentinel-3/SLSTR. Stereo-wind products are validated using clear-sky terrain measurements, spaceborne LiDAR, and reanalysis winds for winter and summer over both poles. Applications of multi-LEO polar stereo winds range from polar atmospheric circulation to nighttime cloud identification. Low cloud detection during polar nighttime is extremely challenging for satellite remote sensing. The stereo-winds method can improve polar cloud observations in otherwise challenging conditions.
Dataset of stereo and multi-channel IRs for a 50-point Lebedev quadrature.
<p>We present a free dataset of Impulse Response measurements for all positions on a 50-point Lebedev arranged loudspeaker array for a variety of stereo microphone configurations, 32 Eigenmic capsules, and up to 4th Order Ambisonics. This dataset has particular relevance for those interested in training novel stereo to ambisonic upmix algorithms. </p>
HPE using Stereo Vision with 3D Landmarks
<p>The present video shows the system's capabilities to perform the head pose estimation in yaw, pitch, and roll angles. It can be seen the response time of the system in comparison with the subject movement.</p>
Mesoscale stereo retrievals from Hunga Tonga-Hunga Ha’apai Eruption of 15 January 2022
Open the record for dataset details and reuse information.
An integrated baseline assessment of reef sharks around Saba (Dutch Caribbean), combining three methods: stereo-BRUVs, Telemetry and Citizen Science.
Open the record for dataset details and reuse information.
Data for: Multi-LEO satellite stereo winds
Open the record for dataset details and reuse information.
2m Digital Terrain Model Combining LIDAR and Stereo-Enhanced Photogrammetric Data, Niwot Ridge LTER Project Area, Colorado
Citation: Manley, W.F., Parrish, E.G., and Lestak, L.R., 2009, High-Resolution Orthorectified Imagery and Digital Elevation Models for Study of Environmental Change at Niwot Ridge and Green Lakes Valley, Colorado: Niwot Ridge LTER, INSTAAR, University of Colorado at Boulder, digital media. This dataset is a Digital Terrain Model (DTM) for the Niwot Ridge Long Term Ecological Research (LTER) project area at 2 m resolution, and is well suited for hydrologic modeling and other analyses of bare-earth terrain. The DTM is derived from the first reflective surface or a Digital Surface Model (DSM) that was created from 12 micron digital stereo aerial photography. Elevation points were both automatically filtered and hand-adjusted to better represent bare earth conditions. Green Lakes Valley LiDAR (Light Detection and Ranging) point data were appended to the filtered and edited data. Breakline information (ie. ridge tops, lake edges, and streams) was added. A final 2 meter gridded DTM and shaded relief model was then generated. The DTM is useful for terrain analysis and derivation of layers such as slope angle, aspect, shaded relief images, and contours. The DTM and shaded relief model covers a total area of 98 km2 and is available in Environmental Systems Research Institute's (ESRI's) GRID format for a total dataset size of 125 MB. They share a UTM zone 13 projection, NAD83 horizontal datum and NAVD88 vertical datum, with FGDC-compliant metadata. The DTM is available through an unrestricted public license, and can be obtained online or on DVD by request (see Distributor contact information below). Imagery available in this series includes orthorectified aerial photography for 1953, 1972, 1985, 1990, 1999, 2000, 2002, 2004, 2006 and 2008. Together, the digital elevation models and imagery will be of interest to land managers, scientists, and others for observation and analysis of natural features and ecosystems. NOTE: This EML metadata file does not contain important geospat
2m Digital Terrain Shaded Relief Model Combining LIDAR and Stereo-Enhanced Photogrammetric Data, Niwot Ridge LTER Project Area, Colorado
Citation: Manley, W.F., Parrish, E.G., and Lestak, L.R., 2009, High-Resolution Orthorectified Imagery and Digital Elevation Models for Study of Environmental Change at Niwot Ridge and Green Lakes Valley, Colorado: Niwot Ridge LTER, INSTAAR, University of Colorado at Boulder, digital media. This dataset is a Digital Terrain Shaded Relief Model (DTM) for the Niwot Ridge Long Term Ecological Research (LTER) project area at 2 m resolution, and is well suited for visualization of bare-earth terrain. The DTM is derived from the first reflective surface or a Digital Surface Model (DSM) that was created from 12 micron digital stereo aerial photography. Elevation points were both automatically filtered and hand-adjusted to better represent bare earth conditions. Green Lakes Valley LiDAR (Light Detection and Ranging) point data were appended to the filtered and edited data. Breakline information (ie. ridge tops, lake edges, and streams) was added. A final 2 meter gridded DTM and shaded relief model was then generated. The DTM is useful for terrain analysis and derivation of layers such as slope angle, aspect, shaded relief images, and contours. The DTM and shaded relief model covers a total area of 98 km2 and is available in Environmental Systems Research Institute's (ESRI's) GRID format for a total dataset size of 125 MB. They share a UTM zone 13 projection, NAD83 horizontal datum and NAVD88 vertical datum, with FGDC-compliant metadata. The DTM is available through an unrestricted public license, and can be obtained online or on DVD by request (see Distributor contact information below). Imagery available in this series includes orthorectified aerial photography for 1953, 1972, 1985, 1990, 1999, 2000, 2002, 2004, 2006 and 2008. Together, the digital elevation models and imagery will be of interest to land managers, scientists, and others for observation and analysis of natural features and ecosystems. NOTE: This EML metadata file does not contain important geospatial data pr
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.