Search results for "VDP::Food science and technology: 600"

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Automatic Calibration of an Industrial RGB-D Camera Network Using Retroreflective Fiducial Markers

2019

This paper describes a non-invasive, automatic, and robust method for calibrating a scalable RGB-D sensor network based on retroreflective ArUco markers and the iterative closest point (ICP) scheme. We demonstrate the system by calibrating a sensor network comprised of six sensor nodes positioned in a relatively large industrial robot cell with an approximate size of 10 m × 10 m × 4 m . Here, the automatic calibration achieved an average Euclidean error of 3 c m at distances up to 9.45 m . To achieve robustness, we apply several innovative techniques: Firstly, we mitigate the ambiguity problem that occurs when detecting a marker at long range or low resolution by comparing the…

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologylcsh:Chemical technologytime-of-flightBiochemistryArticleVDP::Food science and technology: 600Analytical Chemistrylaw.inventionIndustrial robotlawRegion of interestRobustness (computer science)automatic calibration0202 electrical engineering electronic engineering information engineeringCalibrationVDP::Næringsmiddelteknologi: 600lcsh:TP1-1185Computer visionElectrical and Electronic EngineeringInstrumentationbusiness.industryambiguity problemIterative closest point3D sensors020207 software engineeringretroreflective markersAtomic and Molecular Physics and OpticsTime of flightTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESRGB color model020201 artificial intelligence & image processingArtificial intelligencebusinessFiducial markerWireless sensor networkSensors
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