Search results for "Face Recognition"

showing 10 items of 23 documents

Visual Impairment Is Associated With Depressive Symptoms—Results From the Nationwide German DEGS1 Study

2018

Introduction: Visual impairment is associated with a variety of co-morbidities including physical and mental health in industrial countries. Our aim is to examine associations between self-reported impairment and depressive symptoms in the German population. Methods: The point prevalence of self-reported visual impairment in Germany was computed using data from the German Health Interview and Examination Survey for adults from 2008 to 2011 (N=7.783, 50.5% female, age range 18-79 years). Visual impairment was surveyed by two questions, one for seeing faces at a distance of 4 meters and one for reading newspapers. Depressive symptoms were evaluated with the PHQ-9 questionnaire and two-week pr…

medicine.medical_specialtygenetic structureslcsh:RC435-571Visual impairmentPopulationPrevalencevisual impairmentLogistic regressionPatient Health Questionnaire-903 medical and health sciences0302 clinical medicinedepressive symptomsreadinglcsh:PsychiatryEpidemiologyMedicine030212 general & internal medicineeducationDepression (differential diagnoses)Original ResearchPsychiatryeducation.field_of_studybusiness.industryConfoundingmedicine.diseaseComorbidityPsychiatry and Mental health030221 ophthalmology & optometryepidemiologymedicine.symptombusinessClinical psychologyface recognitionFrontiers in Psychiatry
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Age, gender, and puberty influence the development of facial emotion recognition

2015

Our ability to differentiate between simple facial expressions of emotion develops between infancy and early adulthood, yet few studies have explored the developmental trajectory of emotion recognition using a single methodology across a wide age-range. We investigated the development of emotion recognition abilities through childhood and adolescence, testing the hypothesis that children’s ability to recognise simple emotions is modulated by chronological age, pubertal stage and gender. In order to establish norms, we assessed 478 children aged 6-16 years, using the Ekman-Friesen Pictures of Facial Affect. We then modelled these cross-sectional data in terms of competence in accurate recogn…

child developmentlcsh:Psychologylcsh:BF1-990emotion recognition150Psychologyemotionadolescencesocial cognitionfacial expressionOriginal Researchface recognition
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Does Holistic Processing Require a Large Brain? Insights From Honeybees and Wasps in Fine Visual Recognition Tasks

2018

The expertise of humans for recognizing faces is largely based on holistic processing mechanism, a sophisticated cognitive process that develops with visual experience. The various visual features of a face are thus glued together and treated by the brain as a unique stimulus, facilitating robust recognition. Holistic processing is known to facilitate fine discrimination of highly similar visual stimuli, and involves specialized brain areas in humans and other primates. Although holistic processing is most typically employed with face stimuli, subjects can also learn to apply similar image analysis mechanisms when gaining expertise in discriminating novel visual objects, like becoming exper…

lcsh:Psychologyhierarchical stimulihymenopteranslcsh:BF1-990Apis melliferaholistic processingconfigural processingface recognitionFrontiers in Psychology
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Time Unification on Local Binary Patterns Three Orthogonal Planes for Facial Expression Recognition

2019

International audience; Machine learning has known a tremendous growth within the last years, and lately, thanks to that, some computer vision algorithms started to access what is difficult or even impossible to perceive by the human eye. While deep learning based computer vision algorithms have made themselves more and more present in the recent years, more classical feature extraction methods, such as the ones based on Local Binary Patterns (LBP), still present a non negligible interest, especially when dealing with small datasets. Furthermore, this operator has proven to be quite useful for facial emotions and human gestures recognition in general. Micro-Expression (ME) classification is…

human eyeHistogramsgeometryUnificationComputer scienceLocal binary patternsoptimisationFeature extraction02 engineering and technologyhuman gestures recognitionFacial recognition systemcomputer visionVideos[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]time unification method03 medical and health sciences0302 clinical medicineMathematical modelLBPemotion recognition0202 electrical engineering electronic engineering information engineeringfacial emotionsfacial expression recognitionlocal binary patternsFace recognitionContextual image classificationArtificial neural networkbusiness.industryDeep learningdeep learning[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitionComputational modelingmicroexpression classificationInterpolationorthogonal planesneural netsmachine learning[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Micro expressionFeature extraction020201 artificial intelligence & image processinglearning (artificial intelligence)Artificial intelligencebusiness030217 neurology & neurosurgeryGestureimage classification
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Does Holistic Processing Require a Large Brain? Insights From Honeybees and Wasps in Fine Visual Recognition Tasks

2018

International audience

[SCCO]Cognitive science[SCCO.NEUR]Cognitive science/Neuroscience[SDV.BA]Life Sciences [q-bio]/Animal biology[SCCO.PSYC]Cognitive science/PsychologyComputingMilieux_MISCELLANEOUSApis mellifera; configural processing; face recognition; hierarchical stimuli; holistic processing; hymenopterans; Vespula vulgaris; visual cognition
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Local operators to detect regions of interest

1997

The performance of a visual system is strongly influenced by the information processing that is done in the early vision phase. The need exists to limit the computation on areas of interest to reduce the total amount of data and their redundancy. This paper describes a new method to drive the attention during the analysis of complex scenes. Two new local operators, based on the computation of local moments and symmetries, are combined to drive the selection. Experimental results on real data are also reported. © 1997 Elsevier Science B.V.

ComputationEarly visioncomputer.software_genreMachine learningFacial recognition systemSegmentationArtificial IntelligenceRedundancy (engineering)Selection (linguistics)AttentionSegmentationLimit (mathematics)Face recognitionElectrical and Electronic Engineering1707MathematicsSettore INF/01 - Informaticabusiness.industryInformation processingSignal ProcessingSymmetry operatorComputer Vision and Pattern RecognitionArtificial intelligenceData miningbusinesscomputerSoftwarePattern Recognition Letters
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Spectral interest points and texture extraction and fusion for identification, control and security

2018

Biometrics is an emerging technology that proposes new methods of control, identification and security. Biometric systems are often subject to risks. Face recognition is popular and several existing approaches use images in the visible spectrum. These traditional systems operating in the visible spectrum suffer from several limitations due to changes in lighting, poses and facial expressions. The methodology presented in this thesis is based on multispectral facial recognition using infrared and visible imaging, to improve the performance of facial recognition and to overcome the deficiencies of the visible spectrum. The multispectral images used in this study are obtained by fusion of visi…

Reconnaissance de visage[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Visible infrarougeAnalyse multi-ComposanteDescripteurDetectorTextureDescriptorFace recognitionDetecteurVisible infraredMultimodal analysis
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The Development of Perceptual Sensitivity to Second-Order Facial Relations in Children

2010

This study investigated children's perceptual ability to process second-order facial relations. In total, 78 children in three age groups (7, 9, and 11 years) and 28 adults were asked to say whether the eyes were the same distance apart in two side-by-side faces. The two faces were similar on all points except the space between the eyes, which was either the same or different, with various degrees of difference. The results showed that the smallest eye spacing children were able to discriminate decreased with age. This ability was sensitive to face orientation (upright or upside-down), and this inversion effect increased with age. It is concluded here that, despite early sensitivity to conf…

AdultMalemedicine.medical_specialtyConfigural informationVisual perceptionAdolescentmedia_common.quotation_subject[SHS.PSY]Humanities and Social Sciences/PsychologyExperimental and Cognitive PsychologyAudiologyFacial recognition system050105 experimental psychologyDevelopmental psychologyYoung Adult[ SHS.PSY ] Humanities and Social Sciences/PsychologyChild DevelopmentDiscrimination PsychologicalMental ProcessesDevelopmental courseDevelopment offace recognition abilitiesPerceptionDevelopmental and Educational PsychologymedicineFace processingHumans0501 psychology and cognitive sciencesSensitivity (control systems)10. No inequalityChildChildrenComputingMilieux_MISCELLANEOUSSecond-order relationsmedia_common05 social sciencesInformation processingAge FactorsCognitionRecognition PsychologyPattern Recognition VisualFace (geometry)Face[SCCO.PSYC]Cognitive science/PsychologyTask analysisFemalePsychology050104 developmental & child psychology
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Multispectral image denoising with optimized vector non-local mean filter

2016

Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …

FOS: Computer and information sciencesMulti-spectral imaging systemsComputer Vision and Pattern Recognition (cs.CV)Optimization frameworkMultispectral imageComputer Science - Computer Vision and Pattern Recognition02 engineering and technologyWhite noisePixels[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringComputer visionUnbiased risk estimatorMultispectral imageMathematicsMultispectral imagesApplied MathematicsBilateral FilterNumerical Analysis (math.NA)Non-local meansAdditive White Gaussian noiseStein's unbiased risk estimatorIlluminationComputational Theory and MathematicsRestorationImage denoisingsymbols020201 artificial intelligence & image processingNon-local mean filtersComputer Vision and Pattern RecognitionStatistics Probability and UncertaintyGaussian noise (electronic)Non- local means filtersAlgorithmsNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFace Recognitionsymbols.namesakeNoise RemovalArtificial IntelligenceFOS: MathematicsParameter estimationMedian filterMathematics - Numerical AnalysisElectrical and Electronic EngineeringFusionPixelbusiness.industryVector non-local mean filter020206 networking & telecommunicationsPattern recognitionFilter (signal processing)Bandpass filters[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsStein's unbiased risk estimators (SURE)NoiseAdditive white Gaussian noiseComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingArtificial intelligenceReconstructionbusinessModel
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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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