Search results for "3d registration"

showing 7 items of 7 documents

Integration of high resolution spatial and spectral data acquisition systems for monitoring purposes in cultural heritage applications

2013

The concern and interest of this PhD thesis is the registration of featureless 3D and multispectral datasets describing cultural heritage objects.In this context, there are few natural salient features between the complementary datasets, and the use of targets is generally proscribed.We thus develop a technique based on the photogrammetric tracking of the acquisition systems in use.A series of simulations was performed to evaluate the accuracy of our method in three configurations chosen to represent a variety of cultural heritage objects.These simulations show that we can achieve a spatial tracking accuracy of 0.020 mm and an angular accuracy of 0.100 mrad using four 5 Mpx cameras when dig…

[SPI.OTHER]Engineering Sciences [physics]/OtherCalibrations optiques[ SPI.OTHER ] Engineering Sciences [physics]/Other[SPI.OTHER] Engineering Sciences [physics]/Other[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Étude du patrimoinePhotogrammétrie3D digitizationImagerie multispectrale[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Multispectral imagingOptical calibration2D-3D registrationRecalage 2D – 3DCultural heritageClose range photogrammetry[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]Numérisation 3D
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LMI-based 2D-3D Registration: from Uncalibrated Images to Euclidean Scene

2015

International audience; This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates , and two or more uncalibrated cameras. An unknown subset of the scanned points have their image projections detected and matched across images. The proposed approach assumes the cameras only known in some arbitrary projective frame and no calibration or autocalibration is required. The devised solution is based on a Linear Matrix Inequality (LMI) framework that allows simultaneously estimating the projective transformation relating the cameras to the scene and establishing 2D-3D correspondences without triangulating image points. The proposed LMI framewo…

0209 industrial biotechnology3d registrationPixelbusiness.industry[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]Linear matrix inequalityComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registration[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020901 industrial engineering & automation[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Robustness (computer science)Projective frameComputer Science::Computer Vision and Pattern RecognitionEuclidean geometry0202 electrical engineering electronic engineering information engineering[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessMathematics
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Registration of arbitrary multi-view 3D acquisitions

2013

International audience; To register 3D meshes representing smooth surfaces we track the 3D digitization system using photogrammetric techniques and calibrations. We present an example by digitizing a 800 mm x 600 mm portion of a car door. To increase the tracking accuracy the 3D scanner is placed in a cubic frame of side 0.5 m covered with 78 targets. The target frame moves in a volume that is approximately 1100 mm x 850 mm x 900 mm, to digitize the area of interest. Using four cameras this target frame is tracked with of an accuracy of 0.03 mm spatially and 0.180 mrad angularly. A registration accuracy between 0.1 mm and 2 mm is reached. This method can be used for the registration of mesh…

Scanner[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingGeneral Computer Science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer science[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyTracking (particle physics)01 natural sciences010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing3D imagingComputer graphics (images)0103 physical sciences0202 electrical engineering electronic engineering information engineeringPolygon meshComputer visionDigitization[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryClose-range photogrammetryTrack (disk drive)020208 electrical & electronic engineeringFrame (networking)General Engineering3D registrationPhotogrammetryMulti-view registrationArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingVolume (compression)Computers in Industry
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Localization of 2D Cameras in a Known Environment Using Direct 2D-3D Registration

2014

International audience; In this paper we propose a robust and direct 2D-to- 3D registration method for localizing 2D cameras in a known 3D environment. Although the 3D environment is known, localizing the cameras remains a challenging problem that is particularly undermined by the unknown 2D-3D correspondences, outliers, scale ambiguities and occlusions. Once the cameras are localized, the Structure-from-Motion reconstruction obtained from image correspondences is refined by means of a constrained nonlinear optimization that benefits from the knowledge of the scene. We also propose a common optimization framework for both localization and refinement steps in which projection errors in one v…

3d registrationbusiness.industry[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionIterative reconstructionImage (mathematics)Nonlinear programmingHistogramOutlier[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionArtificial intelligenceScale (map)Projection (set theory)businessMathematics2014 22nd International Conference on Pattern Recognition
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SAMSLAM: Simulated Annealing Monocular SLAM

2013

This paper proposes a novel monocular SLAM approach. For a triplet of successive keyframes, the approach inteleaves the registration of the three 3D maps associated to each image pair in the triplet and the refinement of the corresponding poses, by progressively limiting the allowable reprojection error according to a simulated annealing scheme. This approach computes only local overlapping maps of almost constant size, thus avoiding problems of 3D map growth. It does not require global optimization, loop closure and back-correction of the poses.

3D RegistrationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniRANSACSettore INF/01 - InformaticaComputer scienceDisparityComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONReprojection errorLimitingStructure from MotionPose EstimationLoop closureComputer Science::Computer Vision and Pattern RecognitionSLAMSimulated annealingImage pairMonocular slamSimulated AnnealingConstant (mathematics)Global optimizationAlgorithmVisual SLAMFeature Matching
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Registration of 3D and Multispectral Data for the Study of Cultural Heritage Surfaces

2013

International audience; We present a technique for the multi-sensor registration of featureless datasets based on the photogrammetric tracking of the acquisition systems in use. This method is developed for the in situ study of cultural heritage objects and is tested by digitizing a small canvas successively with a 3D digitization system and a multispectral camera while simultaneously tracking the acquisition systems with four cameras and using a cubic target frame with a side length of 500 mm. The achieved tracking accuracy is better than 0.03 mm spatially and 0.150 mrad angularly. This allows us to seamlessly register the 3D acquisitions and to project the multispectral acquisitions on th…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyclose range photogrammetryTracking (particle physics)computer.software_genrelcsh:Chemical technologyBiochemistryArticle3D digitizationAnalytical Chemistry[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing11. Sustainability2D-3D registration0202 electrical engineering electronic engineering information engineeringmultispectral imagingComputer visionlcsh:TP1-1185Electrical and Electronic EngineeringInstrumentationDigitization[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMultispectral dataMultimediabusiness.industryFrame (networking)020207 software engineeringcultural heritageAtomic and Molecular Physics and Opticsoptical calibrationCultural heritagePhotogrammetrydigitization020201 artificial intelligence & image processingArtificial intelligencebusinesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSensors
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Asserting the Precise Position of 3D and Multispectral Acquisition Systems for Multisensor Registration Applied to Cultural Heritage Analysis

2012

International audience; We present a novel method to register multispectral acquisitions on a 3D model. The method is based on the external tracking of the acquisition systems using close-range photogrammetric techniques: multiple calibrated cameras simultaneously observe the successive acquisition systems in use. The views from these cameras are used to precisely determine the position of each acquisition system. All datasets can then be projected in the same coordinate system. The registration is thus independent from the quality and content of the data. This method is well suited to the study of cultural heritage or any other application where we do not wish to place targets on the objec…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceCoordinate systemMultispectral image02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingclose range photogrammetryTracking (particle physics)multispectral acquisitions[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingPosition (vector)0202 electrical engineering electronic engineering information engineeringComputer vision[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing2d-3d registrationbusiness.industry020207 software engineeringcultural heritageObject (computer science)Pipeline (software)optical calibrationCultural heritage3d digitizationPhotogrammetry020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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