Search results for "Iterative closest point"

showing 9 items of 9 documents

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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Accuracy between virtual surgical planning and actual outcomes in orthognathic surgery by iterative closest point algorithm and color maps: A retrosp…

2018

Background To evaluate the accuracy between actual outcomes and virtual surgical planning (VSP) in orthognathic surgery regarding the use of three-dimensional (3D) surface models for registration using iterative closest point (ICP) algorithm and generated color maps. Material and Methods Construction of planning and postoperative 3D models in STL files format (M0 and M1, respectively) from CBCT of 25 subjects who had been submitted to bimaxillary orthognathic surgery was performed. M0 and M1 were sent to Geomagic software in semi-automatic alignment surface mesh order of M0 and M1 for registration using ICP algorithm to calculate mean deviation (MD, MD+, MD-, SD) and root mean square (RMS –…

AdultMaleComputer sciencemedicine.medical_treatmentOrthognathic surgery3d modelMandibleNoseSurgical planningPatient Care PlanningRoot mean square03 medical and health sciencesImaging Three-Dimensional0302 clinical medicineSoftwareMaxillamedicineHumansGeneral DentistryRetrospective StudiesReproducibilityOrthognathic Surgical Proceduresbusiness.industryResearchOrthognathic SurgeryReproducibility of ResultsIterative closest pointRetrospective cohort study030206 dentistryCone-Beam Computed Tomography:CIENCIAS MÉDICAS [UNESCO]Treatment OutcomeSurgery Computer-AssistedOtorhinolaryngologyUNESCO::CIENCIAS MÉDICASComputer-Aided DesignFemaleSurgeryOral SurgerybusinessAlgorithmAlgorithmsMedicina Oral Patología Oral y Cirugia Bucal
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ConformalALU: A Conformal Geometric Algebra Coprocessor for Medical Image Processing

2015

Medical imaging involves important computational geometric problems, such as image segmentation and analysis, shape approximation, three-dimensional (3D) modeling, and registration of volumetric data. In the last few years, Conformal Geometric Algebra (CGA), based on five-dimensional (5D) Clifford Algebra, is emerging as a new paradigm that offers simple and universal operators for the representation and solution of complex geometric problems. However, the widespread use of CGA has been so far hindered by its high dimensionality and computational complexity. This paper proposes a simplified formulation of the conformal geometric operations (reflections, rotations, translations, and uniform …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCoprocessorComputer scienceClifford algebraConformal geometric algebraConformal mapImage processingParallel computingImage segmentationComputational geometryTheoretical Computer ScienceGeometric algebraOperator (computer programming)Computational Theory and MathematicsConformal geometric algebra five-dimensional clifford algebra computational geometry embedded coprocessors systems-on-programmable-chip FPGA-based prototyping medical imaging segmentation 3D modeling Volume registration Growing Neural Gas marching spheres iterative closest point (ICP) thin-plate spline robust point matching (TPS-RPM)Hardware and ArchitectureScalingSoftwareIEEE Transactions on Computers
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Method for 3D fibre reconstruction on a microrobotic platform

2015

Automated handling of a natural fibrous object requires a method for acquiring the three-dimensional geometry of the object, because its dimensions cannot be known beforehand. This paper presents a method for calculating the three-dimensional reconstruction of a paper fibre on a microrobotic platform that contains two microscope cameras. The method is based on detecting curvature changes in the fibre centreline, and using them as the corresponding points between the different views of the images. We test the developed method with four fibre samples and compare the results with the references measured with an X-ray microtomography device. We rotate the samples through 16 different orientatio…

0209 industrial biotechnologyHistologyMicroscopeComputer sciencebusiness.industryOrientation (computer vision)3D reconstructionIterative closest point02 engineering and technologyRepeatabilityCurvatureSample (graphics)Pathology and Forensic Medicinelaw.invention020901 industrial engineering & automationlaw0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionSensitivity (control systems)Artificial intelligencebusinessJournal of Microscopy
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Computer vision-based approach for rite decryption in old societies

2015

International audience; This paper presents an approach to determine the spatial arrangement of bones of horses in an excavation site and perform the 3D reconstruction of the scene. The relative 3D positioning of the bones was computed exploiting the information in images acquired at different levels, and used to relocate provided 3D models of the bones. A novel semi-supervised approach was proposed to generate dense point clouds of the bones from sparse features. The point clouds were later matched with the given models using Iterative Closest Point (ICP).

RiteComputer sciencebusiness.industry[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO]3D reconstructionFeature extraction[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]Point cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONIterative closest pointExcavationIterative reconstructionSolid modeling[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionArtificial intelligencebusinessComputingMethodologies_COMPUTERGRAPHICS
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A Novel Digital Technique for Measuring the Accuracy of an Indirect Bonding Technique Using Fixed Buccal Multibracket Appliances

2021

The aim of this study was to analyze the accuracy and predictability of the indirect bonding technique of fixed buccal multibracket appliances using a customized iterative closest point algorithm. Materials and Methods: A total of 340 fixed buccal multibracket appliances were virtually planned and bonded on 34 experimental anatomically based acrylic resin models by using orthodontic templates designed and manufactured to indirectly bond the fixed buccal multibracket appliances. Afterwards, the models were submitted to a three-dimensional impression technique by an intraoral scanner, and the standard tessellation language digital files from the virtual planning and the digital impression wer…

OrthodonticsIntraoral scannerTessellation (computer graphics)accuracydigitalRMedicine (miscellaneous)Iterative closest pointBuccal administrationorthodontics; digital; morphometry; accuracy; indirect bondingArticleImpressionVirtual planningindirect bondingMedicineTorqueorthodonticsRotation (mathematics)morphometryMathematicsJournal of Personalized Medicine
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Automatic landmark detection and 3D Face data extraction

2017

Abstract This paper contributes to 3D facial synthesis by presenting a novel method for parameterization using Landmark Point detection. The approach presented aims at improving facial recognition even in varying facial expressions, and missing data in 3D facial models. As such, the prime objective was to develop an automatically embedded process that can detect any frontal face in 3D face recognition systems, with face segmentation and surface curvature information. Using the hybrid interpolation method, experiments on facial landmarks were performed on 4950 images from Face Recognition Grand Challenge database (FRGC). Distinctive facial landmarks from the nose–tips, Limits mouth and two e…

Face hallucinationGeneral Computer ScienceComputer sciencebusiness.industry05 social sciencesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION050301 educationIterative closest pointPattern recognition02 engineering and technologyLandmark pointFace Recognition Grand ChallengeFacial recognition systemTheoretical Computer SciencePoint distribution modelModeling and Simulation0202 electrical engineering electronic engineering information engineeringThree-dimensional face recognition020201 artificial intelligence & image processingComputer visionArtificial intelligenceFace detectionbusiness0503 educationJournal of Computational Science
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Visual Marker Guided Point Cloud Registration in a Large Multi-Sensor Industrial Robot Cell

2018

This paper presents a benchmark and accuracy analysis of 3D sensor calibration in a large industrial robot cell. The sensors used were the Kinect v2 which contains both an RGB and an IR camera measuring depth based on the time-of-flight principle. The approach taken was based on a novel procedure combining Aruco visual markers, methods using region of interest and iterative closest point. The calibration of sensors is performed pairwise, exploiting the fact that time-of-flight sensors can have some overlap in the generated point cloud data. For a volume measuring 10m × 14m × 5m a typical accuracy of the generated point cloud data of 5–10cm was achieved using six sensor nodes.

Computer sciencebusiness.industry010401 analytical chemistryPoint cloudIterative closest pointCloud computing02 engineering and technology01 natural sciences0104 chemical sciencesVisualizationlaw.inventionIndustrial robotlaw0202 electrical engineering electronic engineering information engineeringBenchmark (computing)CalibrationRGB color model020201 artificial intelligence & image processingComputer visionArtificial intelligencebusiness2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)
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3D Reconstruction of Dynamic Vehicles using Sparse 3D-Laser-Scanner and 2D Image Fusion

2016

International audience; Map building becomes one of the most interesting research topic in computer vision field nowadays. To acquire accurate large 3D scene reconstructions, 3D laser scanners are recently developed and widely used. They produce accurate but sparse 3D point clouds of the environments. However, 3D reconstruction of rigidly moving objects along side with the large-scale 3D scene reconstruction is still lack of interest in many researches. To achieve a detailed object-level 3D reconstruction, a single scan of point cloud is insufficient due to their sparsity. For example, traditional Iterative Closest Point (ICP) registration technique or its variances are not accurate and rob…

RegistrationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPoint cloud02 engineering and technologyIterative reconstructionRANSAC[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Robustness (computer science)Point Cloud0202 electrical engineering electronic engineering information engineeringComputer visionImage fusionbusiness.industry3D reconstruction[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Iterative closest point2D camera020207 software engineeringICP3D cameraMaxima and minimaGeography020201 artificial intelligence & image processingArtificial intelligencebusiness3D Reconstruction
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