Real-time multiview data fusion for object tracking with RGBD sensors

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dc.contributor.authorAmamra, Abdenour
dc.contributor.authorAouf, Nabil
dc.date.accessioned2023-09-20T11:38:50Z
dc.date.available2023-09-20T11:38:50Z
dc.date.issued2014-12-01
dc.description.abstractThis paper presents a new approach to accurately track a moving vehicle with a multiview setup of red-green-blue depth (RGBD) cameras. We first propose a correction method to eliminate a shift, which occurs in depth sensors when they become worn. This issue could not be otherwise corrected with the ordinary calibration procedure. Next, we present a sensor-wise filtering system to correct for an unknown vehicle motion. A data fusion algorithm is then used to optimally merge the sensor-wise estimated trajectories. We implement most parts of our solution in the graphic processor. Hence, the whole system is able to operate at up to 25 frames per second with a configuration of five cameras. Test results show the accuracy we achieved and the robustness of our solution to overcome uncertainties in the measurements and the modelling.en_UK
dc.identifier.citationAmamra A, Aouf N. (2016) Real-time multiview data fusion for object tracking with RGBD sensors, Robotica, Volume 34, Issue 8, August 2016, pp. 1855-1879en_UK
dc.identifier.eissn1469-8668
dc.identifier.issn0263-5747
dc.identifier.urihttps://doi.org/10.1017/S026357471400263X
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20259
dc.language.isoenen_UK
dc.publisherCambridge University Press (CUP)en_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectRGBDen_UK
dc.subjectReal-timeen_UK
dc.subjectTrackingen_UK
dc.subjectMultiviewen_UK
dc.subjectKalman filteren_UK
dc.subjectRobust H∞en_UK
dc.subjectCovariance intersectionen_UK
dc.subjectGPUen_UK
dc.titleReal-time multiview data fusion for object tracking with RGBD sensorsen_UK
dc.typeArticleen_UK

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