Отрывок: We choose one camera as reference to which other cameras are calibrated. The second procedure performs a full camera calibration, i.e., it computes intrinsic and extrinsic parameters, by finding numerous 3D point matches between pairs of adjacent cameras. We select a less computationally expensive solution; that is, the R-Nearest Neighbor [8], which is described below. First, apply the transformations obtained during the pre-calibration step to ...
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dc.contributor.authorRuchay, A.N.-
dc.contributor.authorKolpakov V.I.-
dc.contributor.authorDorofeev, K.A.-
dc.date.accessioned2018-05-14 17:33:46-
dc.date.available2018-05-14 17:33:46-
dc.date.issued2018-
dc.identifierDspace\SGAU\20180514\69188ru
dc.identifier.citationRuchay A.N. Fusion of information from multiple Kinect sensorsfor 3D object reconstruction / A.N. Ruchay, K.A. Dorofeev, V.I. Kolpakov // Сборник трудов IV международной конференции и молодежной школы «Информационные технологии и нанотехнологии» (ИТНТ-2018) - Самара: Новая техника, 2018. - С.1221-1226ru
dc.identifier.urihttp://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Fusion-of-information-from-multiple-Kinect-sensors-for-3D-object-reconstruction-69188-
dc.descriptionОсновная статьяru
dc.description.abstractIn this paper, we estimate the accuracy of 3D object reconstruction using multiple Kinect sensors. First, we discuss the calibration of multiple Kinect sensors, and provide an analysis of the accuracy and resolution of its the depth data. Next, the precision of coordinate mapping between sensors data for registration of depth and color images is evaluated. We test a system with four Kinect V2 sensors and present reconstruction accuracy results. Experiments and computer simulation are carried out using Matlab and Kinect V2.ru
dc.language.isoenru
dc.publisherНовая техникаru
dc.subjectmultiple sensors, Kinect, 3D object reconstruction, fusion.ru
dc.titleFusion of information from multiple Kinect sensors for 3D object reconstructionru
dc.typeArticleru
dc.textpartWe choose one camera as reference to which other cameras are calibrated. The second procedure performs a full camera calibration, i.e., it computes intrinsic and extrinsic parameters, by finding numerous 3D point matches between pairs of adjacent cameras. We select a less computationally expensive solution; that is, the R-Nearest Neighbor [8], which is described below. First, apply the transformations obtained during the pre-calibration step to ...-
Располагается в коллекциях: Информационные технологии и нанотехнологии

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