KEvOr dataset [Research data]
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The Kinect Evaluation in Orchard conditions (KEvOr) dataset is comprised of a set of RGB-D captures carried out with the Microsoft Kinect v2 to evaluate the performance of this sensor at different lighting conditions in agricultural orchards and from different distances to the measured target. Three Microsoft Kinect v2 sensors (K2S1, K2S2 and K2S3) were used to scan Fuji apple trees along the afternoon and evening, from the higher sun illuminance (55000 lux) until achieving dark conditions (0.1 lux), obtaining a total of 252 captures: 28 lighting conditions * 3 sensors * 3 repetitions. The data provided for each capture is: the acquired point cloud, illuminance level at the center of the measured scene, and wind speed. The sensors where placed as follows: K2S1: Oriented to the north, measuring the row of trees side under direct sunlight. This sensor was placed at 2.5 m from the measured target. K2S2: Oriented to the north, measuring the row of trees side under direct sunlight. This sensor was placed at 1.5 m from the measured target. K2S3 Oriented to the south, measuring the row of trees side under indirect sunlight. This sensor was placed at 2.5 m from the measured target. The dataset also includes two additional registered captures measuring the same scene from 1.5 m and from 2.5 m.
NoteDades primàries associades a un article publicat a la revista Sensors disponible a l'adreça https://doi.org/10.3390/s20247072
European research projects
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Except where otherwise noted, this item's license is described as cc-by-nc-sa (c) Jordi Gené et al., 2020
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Assessing the Performance of RGB-D Sensors for 3D Fruit Crop Canopy Characterization under Different Operating and Lighting Conditions Gené Mola, Jordi; Llorens Calveras, Jordi; Rosell Polo, Joan Ramon; Gregorio López, Eduard; Arnó Satorra, Jaume; Solanelles Batlle, Francesc; Martínez Casasnovas, José Antonio; Escolà i Agustí, Alexandre (MDPI, 2020-12-10)The use of 3D sensors combined with appropriate data processing and analysis has provided tools to optimise agricultural management through the application of precision agriculture. The recent development of low-cost ...
Rosell Polo, Joan Ramon; Gregorio López, Eduard; Gené Mola, Jordi; Llorens Calveras, Jordi; Torrent Martí, Xavier; Arnó Satorra, Jaume; Escolà i Agustí, Alexandre (Institute of Electrical and Electronics Engineers (IEEE), 2017-02-02)Mobile terrestrial laser scanners (MTLS), based on light detection and ranging (LiDAR) sensors, are used worldwide in agricultural applications. MTLS are applied to characterize the geometry and the structure of plants and ...
Sanz Cortiella, Ricardo; Llorens Calveras, Jordi; Escolà i Agustí, Alexandre; Arnó Satorra, Jaume; Ribes Dasi, Manuel; Masip Vilalta, Joan; Camp, Ferran; Gràcia Aguilà, Felipe José; Solanelles Batlle, Francesc; Planas de Martí, Santiago; Pallejà Cabrè, Tomàs; Palacín Roca, Jordi; Gregorio López, Eduard; Del Moral Martínez, Ignacio; Rosell Polo, Joan Ramon (Molecular Diversity Preservation International (MDPI), 2011)In this work, a LIDAR-based 3D Dynamic Measurement System is presented and evaluated for the geometric characterization of tree crops. Using this measurement system, trees were scanned from two opposing sides to obtain two ...