Search results for " Vision"

showing 10 items of 2709 documents

Extrinsic calibration of heterogeneous cameras by line images

2014

International audience; The extrinsic calibration refers to determining the relative pose of cameras. Most of the approaches for cameras with non-overlapping fields of view (FOV) are based on mirror reflection, object tracking or rigidity constraint of stereo systems whereas cameras with overlapping FOV can be calibrated using structure from motion solutions. We propose an extrinsic calibration method within structure from motion framework for cameras with overlapping FOV and its extension to cameras with partially non-overlapping FOV. Recently, omnidirectional vision has become a popular topic in computer vision as an omnidirectional camera can cover large FOV in one image. Combining the g…

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONBundle adjustment02 engineering and technology01 natural sciences010309 opticsOmnidirectional camera0103 physical sciences11. Sustainability0202 electrical engineering electronic engineering information engineeringStructure from motion[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionOmnidirectional antennaStereo camerasbusiness.industryOrientation (computer vision)Perspective (graphical)[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]Computer Science ApplicationsHardware and ArchitectureVideo tracking020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftware
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Multimodal Images Classification using Dense SURF, Spectral Information and Support Vector Machine

2019

International audience; The multimodal image classification is a challenging area of image processing which can be used to examine the wall painting in the cultural heritage domain. In such classification, a common space of representation is important. In this paper, we present a new method for multimodal representation learning, by using a pixel-wise feature descriptor named dense Speed Up Robust Features (SURF) combined with the spectral information carried by the pixel. For classification of extracted features we have used support vector machine (SVM). Our database was extracted from acquisition on cultural heritage wall paintings that contain four modalities UV, Visible, IRR and fluores…

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologyImage (mathematics)0202 electrical engineering electronic engineering information engineeringFeature descriptorRepresentation (mathematics)Spectral informationSpeeded up robust features SURFGeneral Environmental SciencePixelbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsPattern recognitionSVM classificationSupport vector machineCultural heritageMultimodal imagesCielab spaceDense features[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]General Earth and Planetary Sciences020201 artificial intelligence & image processingArtificial intelligencebusinessFeature learning
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Iteratively Learning a Liver Segmentation Using Probabilistic Atlases: Preliminary Results

2016

This works deals with the concept of liver segmentation by using a priori information based on probabilistic atlases and segmentation learning based of previous steps. A probabilistic atlas is here understood as a probability or membership map that tells how likely is that a point belongs to a shape drawn from the shape distribution at hand. We devise a procedure to segment Perfusion Magnetic Resonance liver images that combines both: a probabilistic atlas of the liver and a segmentation algorithm based on global information of previous simpler segmentation steps, local information from close segmented slices and finally a mathematical morphology procedure, namely viscous reconstruction, to…

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentation02 engineering and technologyIterative reconstructionMathematical morphology030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineSegmentationComputer visionComputingMethodologies_COMPUTERGRAPHICSmedicine.diagnostic_testSegmentation-based object categorizationbusiness.industryProbabilistic logicMagnetic resonance imagingPattern recognitionImage segmentationComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingArtificial intelligencebusinessPerfusion2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)
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A new image segmentation approach using community detection algorithms

2015

Image segmentation has an important role in many image processing applications. Several methods exist for segmenting an image. However, this technique is still a relatively open topic for which various research works are regularly presented. With the recent developments on complex networks theory, image segmentation techniques based on graphs has considerably improved. In this paper, we present a new perspective of image segmentation, by applying three of the most efficient community detection algorithms, Louvain, infomap and stability optimization based on the louvain algorithm, and we extract communities in which the highest modularity feature is achieved. After we show that this measure …

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationImage processing02 engineering and technology[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]03 medical and health sciences0302 clinical medicine[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]Image textureMinimum spanning tree-based segmentation020204 information systems0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Computer visionSegmentationComputingMilieux_MISCELLANEOUSbusiness.industrySegmentation-based object categorization[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]Pattern recognitionImage segmentationRegion growingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithm030217 neurology & neurosurgery2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)
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Automatic skull stripping in MRI based on morphological filters and fuzzy c-means segmentation

2012

In this paper a new automatic skull stripping method for T1-weighted MR image of human brain is presented. Skull stripping is a process that allows to separate the brain from the rest of tissues. The proposed method is based on a 2D brain extraction making use of fuzzy c-means segmentation and morphological operators applied on transversal slices. The approach is extended to the 3D case, taking into account the result obtained from the preceding slice to solve the organ splitting problem. The proposed approach is compared with BET (Brain Extraction Tool) implemented in MRIcro software.

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSensitivity and SpecificityFuzzy logicPattern Recognition AutomatedFuzzy LogicImage Interpretation Computer-AssistedmedicineHumansSegmentationComputer visionSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimedicine.diagnostic_testSkull Stripping Fuzzy C-means Morphological Filters.business.industrySkullProcess (computing)BrainReproducibility of ResultsMagnetic resonance imagingImage segmentationImage EnhancementMagnetic Resonance ImagingSubtraction TechniquePattern recognition (psychology)Skull strippingArtificial intelligenceMr imagesbusinessAlgorithms2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Synchronizing eye tracking and optical motion capture : How to bring them together

2018

Both eye tracking and motion capture technologies are nowadays frequently used in human sciences, although both technologies are usually used separately. However, measuring both eye and body movements simultaneously would offer great potential for investigating cross- modal interaction in human (e.g. music and language-related) behavior. Here we combined an Ergoneers Dikablis head mounted eye tracker with a Qualisys Oqus optical motion cap- ture system. In order to synchronize the recordings of both devices, we developed a gener- alizable solution that does not rely on any (cost-intensive) ready-made / company-provided synchronization solution. At the beginning of each recording, the partic…

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSynchronizingta6121liikkeenkaappausMotion captureeye tracking050105 experimental psychologyMotion (physics)Displacement (vector)Synchronizationliikkeet03 medical and health sciencessilmänliikkeet0302 clinical medicineintermodal processingmotion capture0501 psychology and cognitive sciencesComputer visionVertical displacementseurantaeye movementbusiness.industry05 social sciencesQM1-695metodologiaEye movementmethodologySensory SystemsOphthalmologyHuman anatomyta6131technologykatseenseurantateknologiaEye trackingsynkronointiArtificial intelligenceuusmedialiikkuminennew mediabusinesssynchronization030217 neurology & neurosurgeryResearch ArticleJournal of Eye Movement Research
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Towards a Hierarchical Multitask Classification Framework for Cultural Heritage

2018

Digital technologies such as 3D imaging, data analytics and computer vision opened the door to a large set of applications in cultural heritage. Digital acquisition of a cultural assets takes nowadays a couple of seconds thanks to the achievements in 2D and 3D acquisition technologies. However, enriching these cultural assets with labels and relevant metadata is still not fully automatized especially due to their nature and specificities. With the recent publication of several cultural heritage datasets, many researchers are tackling the challenge of effectively classifying and annotating digital heritage. The challenges that are often addressed are related to visual recognition and image c…

Computer scienceData field02 engineering and technology[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Multitask ClassificationCultural diversity0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Digital preservationComputingMilieux_MISCELLANEOUSContextual image classificationDigital heritagebusiness.industryDeep learningConvolutional Neural Networks[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsData scienceMetadataCultural heritageDigital preservationCultural heritage020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)
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Least-squares community extraction in feature-rich networks using similarity data

2021

We explore a doubly-greedy approach to the issue of community detection in feature-rich networks. According to this approach, both the network and feature data are straightforwardly recovered from the underlying unknown non-overlapping communities, supplied with a center in the feature space and intensity weight(s) over the network each. Our least-squares additive criterion allows us to search for communities one-by-one and to find each community by adding entities one by one. A focus of this paper is that the feature-space data part is converted into a similarity matrix format. The similarity/link values can be used in either of two modes: (a) as measured in the same scale so that one may …

Computer scienceEconomicsKernel FunctionsSocial Sciences02 engineering and technologyLeast squaresInfographicsTranslocation GeneticGeographical LocationsMedical Conditions0202 electrical engineering electronic engineering information engineeringMedicine and Health SciencesPsychologyCluster AnalysisOperator TheoryData ManagementMultidisciplinaryApplied MathematicsSimulation and ModelingQRExperimental PsychologyEuropeFeature (computer vision)Research DesignPhysical SciencesMedicine020201 artificial intelligence & image processingGraphsAlgorithmsNetwork AnalysisNetwork analysisResearch ArticleComputer and Information SciencesScienceFeature vectorScale (descriptive set theory)Research and Analysis MethodsColumn (database)Similarity (network science)020204 information systemsParasitic DiseasesLeast-Squares AnalysisFeature databusiness.industryData VisualizationBiology and Life SciencesPattern recognitionTropical DiseasesEconomic AnalysisMalariaPeople and PlacesArtificial intelligencebusinessMathematicsPLoS ONE
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Experiencing with electronic image stabilization and PRNU through scene content image registration

2021

Abstract This paper explores content-based image registration as a means of dealing with and understanding better Electronic Image Stabilization (EIS) in the context of Photo Response Non-Uniformity (PRNU) alignment. A novel and robust solution to extrapolate the transformation relating the different image output formats for a given device model is proposed. This general approach can be adapted to specifically extract the scale factor (and, when appropriate, the translation) so as to align native resolution images to video frames, with or without EIS on, and proceed to compare PRNU patterns. Comparative evaluations show that the proposed approach outperforms those based on brute-force and p…

Computer scienceElectronic image stabilizationImage registrationContext (language use)Camera and video source identification02 engineering and technology01 natural sciencesMultimedia forensicsArtificial Intelligence0103 physical sciences0202 electrical engineering electronic engineering information engineeringComputer vision010306 general physicsImage registrationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniNative resolutionImage registration Electronic Image Stabilization PRNU Camera and video source identification Multimedia forensicsSettore INF/01 - Informaticabusiness.industryPRNUTracking systemScale factorImage stabilizationIdentification (information)Transformation (function)Signal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftware
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Detection, tracking and event localization of jet stream features in 4-D atmospheric data

2012

We introduce a novel algorithm for the efficient detection and tracking of features in spatiotemporal atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. The algorithm works on data given on a four-dimensional structured grid. Feature selection and clustering are based on adjustable local and global criteria, feature tracking is predominantly based on spatial overlaps of the feature's full volumes. The resulting 3-D features and the identified correspondences between features of consecutive time steps are represented as the nodes and edges of a directed acyclic graph, the event graph. Merging and splitting events appear in…

Computer scienceEvent (computing)lcsh:QE1-996.5Feature selectionGridcomputer.software_genreTracking (particle physics)Directed acyclic graphData segmentlcsh:GeologyFeature (computer vision)Data miningCluster analysiscomputerAlgorithmPhysics::Atmospheric and Oceanic Physics
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