Search results for " image processing."

showing 10 items of 2265 documents

Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study

2014

International audience; Smart camera, i.e. cameras that are able to acquire and process images in real-time, is a typical example of the new embedded computer vision systems. A key example of application is automatic fall detection, which can be useful for helping elderly people in daily life. In this paper, we propose a methodology for development and fast-prototyping of a fall detection system based on such a smart camera, which allows to reduce the development time compared to standard approaches. Founded on a supervised classification approach, we propose a HW/SW implementation to detect falls in a home environment using a single camera and an optimized descriptor adapted to real-time t…

Boosting (machine learning)Computer scienceReal-time computing02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]HW/SW implementationFast smart camera prototypingComputer graphicsReal-time fall detectionZynq0202 electrical engineering electronic engineering information engineering[ INFO.INFO-ES ] Computer Science [cs]/Embedded SystemsSmart cameraArchitectureComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingHome environmentbusiness.industryEfficient algorithm[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]SoC implementation020202 computer hardware & architectureEmbedded systemHardware accelerationBoosting hardware implementation[INFO.INFO-ES]Computer Science [cs]/Embedded Systems020201 artificial intelligence & image processingFall detectionbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingInformation SystemsJournal of Real-Time Image Processing
researchProduct

Real Time Robust Embedded Face Detection Using High Level Description

2011

Face detection is a fundamental prerequisite step in the process of face recognition. It consists of automatically finding all the faces in an image despite the considerable variations of lighting, background, appearance of people, position/orientation of faces, and their sizes. This type of object detection has the distinction of having a very large intra-class, making it a particularly difficult problem to solve, especially when one wishes to achieve real time processing. A human being has a great ability to analyze images. He can extract the information about it and focus only on areas of interest (the phenomenon of attention). Thereafter he can detect faces in an extremely reliable way.…

Boosting (machine learning)business.industryComputer scienceReal-time computingDetector02 engineering and technologyContent-based image retrievalFacial recognition systemObject detection020202 computer hardware & architecture[INFO.INFO-ES] Computer Science [cs]/Embedded Systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer vision[INFO.INFO-ES]Computer Science [cs]/Embedded SystemsArtificial intelligence[ INFO.INFO-ES ] Computer Science [cs]/Embedded SystemsbusinessLinear combinationFace detectionImplementation
researchProduct

Managing Human Factors to Reduce Organisational Risk in Industry

2018

[EN] Human factors are intrinsically involved at virtually any level of most industrial/business activities, and may be responsible for several accidents and incidents, if not correctly identified and managed. Focusing on the significance of human behaviour in industry, this article proposes a multi-criteria decision-making (MCDM)-based approach to support organizational risk assessment in industrial environments. The decision-making trial and evaluation laboratory (DEMATEL) method is proposed as a mathematical framework to evaluate mutual relationships within a set of human factors involved in industrial processes, with the aim of highlighting priorities of intervention. A case study relat…

Bottling processDEMATEL02 engineering and technologylcsh:QA75.5-76.95Multi-criteria decision-makingHuman behaviour0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesInference engineSet (psychology)050107 human factorsRisk managementOrganisational riskbusiness.industryApplied Mathematicslcsh:T57-57.97lcsh:Mathematics05 social sciencesRank (computer programming)General EngineeringMultiple-criteria decision analysislcsh:QA1-939Risk evaluationComputational MathematicsIntervention (law)Risk analysis (engineering)lcsh:Applied mathematics. Quantitative methods020201 artificial intelligence & image processingBusinesslcsh:Electronic computers. Computer scienceRisk assessmentMATEMATICA APLICADA
researchProduct

Class discovery from semi-structured EEG data for affective computing and personalisation

2017

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Many approaches to recognising emotions from metrical data such as EEG signals rely on identifying a very small number of classes and to train a classifier. The interpretation of these classes varies from a single emotion such as stress [24] to features of emotional model such as valence-arousal [4]. There are two major issues here. First classification approach limits the analysis of the data within the selected classes and is also highly dependent on training data/cycles, all of which limits generalisation. Second issue is that it does not exp…

Brain modelingComputer scienceFeature extraction02 engineering and technologyElectroencephalographyMachine learningcomputer.software_genrePersonalizationCorrelationDEAP03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineCluster analysisAffective computingmedicine.diagnostic_testbusiness.industryElectroencephalographySelf-organizing feature mapsFeature extraction020201 artificial intelligence & image processingArtificial intelligenceEmotion recognitionbusinessClassifier (UML)computer030217 neurology & neurosurgery
researchProduct

Mutual information-based feature selection for low-cost BCIs based on motor imagery

2016

In the present study a feature selection algorithm based on mutual information (MI) was applied to electro-encephalographic (EEG) data acquired during three different motor imagery tasks from two dataset: Dataset I from BCI Competition IV including full scalp recordings from four subjects, and new data recorded from three subjects using the popular low-cost Emotiv EPOC EEG headset. The aim was to evaluate optimal channels and band-power (BP) features for motor imagery tasks discrimination, in order to assess the feasibility of a portable low-cost motor imagery based Brain-Computer Interface (BCI) system. The minimal sub set of features most relevant to task description and less redundant to…

Brain-Computer InterfaceSupport Vector MachineDatabases FactualComputer scienceHeadsetSpeech recognitionFeature extractionBiomedical EngineeringReproducibility of ResultHealth InformaticsFeature selection02 engineering and technologyElectroencephalography03 medical and health sciences0302 clinical medicineMotor imagery0202 electrical engineering electronic engineering information engineeringmedicineHumans1707medicine.diagnostic_testbusiness.industryReproducibility of ResultsElectroencephalographyPattern recognitionMutual informationModels TheoreticalAlgorithmSupport vector machineBrain-Computer InterfacesSignal ProcessingSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaEidetic Imagery020201 artificial intelligence & image processingArtificial intelligencebusinessAlgorithms030217 neurology & neurosurgeryHuman2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
researchProduct

Dissimilarity Application for Medical Imaging Classification

2005

In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, alternative ways can be found by constructing decision rules on dissimilarity (distance) representations. In such a recognition process a new object is described by its distances to (a subset of) die training samples. The use of the dissimilarities is especially of interest when features are difficult to obtain or when they have a little discriminative power. Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 col…

Breast cancerDissimilarityComputer assisted diagnosiComputer aided diagnosimammographyCo-occurrence matrixMedical image processingimage segmentationNeural network
researchProduct

Investigating Centrality Measures in Social Networks with Community Structure

2021

Centrality measures are crucial in quantifying the influence of the members of a social network. Although there has been a great deal of work dealing with this issue, the vast majority of classical centrality measures are agnostic of the community structure characterizing many social networks. Recent works have developed community-aware centrality measures that exploit features of the community structure information encountered in most real-world complex networks. In this paper, we investigate the interactions between 5 popular classical centrality measures and 5 community-aware centrality measures using 8 real-world online networks. Correlation as well as similarity measures between both t…

Bridging (networking)Social networkExploitbusiness.industryComputer scienceNode (networking)Community structure02 engineering and technologyComplex networkData science[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI][INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]020204 information systemsSimilarity (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingbusinessCentralityComputingMilieux_MISCELLANEOUS
researchProduct

First M87 Event Horizon Telescope Results. IV. Imaging the Central Supermassive Black Hole

2019

We present the first Event Horizon Telescope (EHT) images of M87, using observations from April 2017 at 1.3 mm wavelength. These images show a prominent ring with a diameter of ~40 μas, consistent with the size and shape of the lensed photon orbit encircling the "shadow" of a supermassive black hole. The ring is persistent across four observing nights and shows enhanced brightness in the south. To assess the reliability of these results, we implemented a two-stage imaging procedure. In the first stage, four teams, each blind to the others' work, produced images of M87 using both an established method (CLEAN) and a newer technique (regularized maximum likelihood). This stage allowed us to av…

Brightness010504 meteorology & atmospheric sciencesgalaxies: jetAstronomyblack hole physicsFOS: Physical sciencesgalaxies: individualtechniques: image processingAstrophysicsGeneral Relativity and Quantum Cosmology (gr-qc)galaxies: individual: M8701 natural sciencesSynthetic dataGeneral Relativity and Quantum Cosmologygalaxies: individual (M87)0103 physical sciencesimage processing [Techniques]010303 astronomy & astrophysicsInstrumentation and Methods for Astrophysics (astro-ph.IM)0105 earth and related environmental sciencesEvent Horizon TelescopePhysicsGround truthSupermassive black holetechniques: high angular resolutionAstronomy and AstrophysicsBlack hole physicsgalaxies: jetsindividual (M87) [Galaxies]Astrophysics - Astrophysics of Galaxiesblack hole physic3. Good healthOrbitInterferometryhigh angular resolution [Techniques]Space and Planetary Sciencetechniques: interferometricAstrophysics of Galaxies (astro-ph.GA)interferometric [Techniques]jets [Galaxies]Deconvolution[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]Astrophysics - Instrumentation and Methods for Astrophysics
researchProduct

Monitoring the Morphology of M87* in 2009-2017 with the Event Horizon Telescope

2020

All authors: Wielgus, Maciek; Akiyama, Kazunori; Blackburn, Lindy; Chan, Chi-kwan; Dexter, Jason; Doeleman, Sheperd S.; Fish, Vincent L.; Issaoun, Sara; Johnson, Michael D.; Krichbaum, Thomas P.; Lu, Ru-Sen; Pesce, Dominic W.; Wong, George N.; Bower, Geoffrey C.; Broderick, Avery E.; Chael, Andrew; Chatterjee, Koushik; Gammie, Charles F.; Georgiev, Boris; Hada, Kazuhiro Loinard, Laurent; Markoff, Sera; Marrone, Daniel P.; Plambeck, Richard; Weintroub, Jonathan; Dexter, Matthew; MacMahon, David H. E.; Wright, Melvyn; Alberdi, Antxon; Alef, Walter; Asada, Keiichi; Azulay, Rebecca; Baczko, Anne-Kathrin; Ball, David; Baloković, Mislav; Barausse, Enrico; Barrett, John; Bintley, Dan; Boland, Wilf…

Brightness1663Active galactic nucleus010504 meteorology & atmospheric sciences1346Event horizonAstronomyAstrophysics::High Energy Astrophysical PhenomenaGalaxy accretion disksFOS: Physical sciencesAstrophysicsF500Astrophysics::Cosmology and Extragalactic Astrophysics01 natural sciences5752033Settore FIS/05 - Astronomia e AstrofisicaSupermassive black holes0103 physical sciencesVery-long-baseline interferometryAstronomy Astrophysics and Cosmology1769010303 astronomy & astrophysicsComputer Vision and Robotics (Autonomous Systems)Astronomy data modelingVery long baseline interferometry0105 earth and related environmental sciences162Black holes; Galaxy accretion disks; Galaxy accretion; Supermassive black holes; Active galactic nuclei; Low-luminosity active galactic nuclei; Very long baseline interferometry; Astronomy data modeling; Radio interferometryEvent Horizon TelescopePhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)Active galactic nucleiSupermassive black holeBlack holesAstronomy and Astrophysics16Galaxy accretion562Position angleGalaxyLow-luminosity active galactic nucleiMedical Image ProcessingSpace and Planetary ScienceRadio interferometryAstrophysics - High Energy Astrophysical Phenomena[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]1859
researchProduct

Roughness and vegetation parameterizations at L-band for soil moisture retrievals over a vineyard field

2015

Abstract The capability of L-band radiometry to monitor surface soil moisture (SM) at global scale has been analyzed in numerous studies, mostly in the framework of the ESA SMOS and NASA SMAP missions. To retrieve SM from L-band radiometric observations, two significant effects have to be accounted for, namely soil roughness and vegetation optical depth. In this study, soil roughness effects on retrieved SM values were evaluated using brightness temperatures acquired by the L-band ELBARA-II radiometer, over a vineyard field at the Valencia Anchor Station (VAS) site during the year 2013. Different combinations of the values of the model parameters used to account for soil roughness effects (…

BrightnessL bandRadiometerMean squared error[SDE.MCG]Environmental Sciences/Global ChangesSoil ScienceGeology15. Life on landL-bandAtmospheric radiative transfer codesL-MEBvegetationCalibrationsoil roughnessRadiometryEnvironmental sciencemicrowave radiometryComputers in Earth Sciencessoil moistureWater content[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUSRemote sensingSMOS
researchProduct