Search results for " Pattern Recognition"

showing 10 items of 1050 documents

Automated Characterization of Mouth Activity for Stress and Anxiety Assessment

2016

International audience; Non-verbal information portrayed by human facial expression, apart from emotional cues also encompasses information relevant to psychophysical status. Mouth activities in particular have been found to correlate with signs of several conditions; depressed people smile less, while those in fatigue yawn more. In this paper, we present a semi-automated, robust and efficient algorithm for extracting mouth activity from video recordings based on Eigen-features and template-matching. The algorithm was evaluated for mouth openings and mouth deformations, on a minimum specification dataset of 640x480 resolution and 15 fps. The extracted features were the signals of mouth expa…

[ INFO ] Computer Science [cs]Computer scienceSpeech recognitionFeature extractionautomatic assessmentComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologymouth gesture recognition[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Yawn[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Correlation03 medical and health sciencesstress0302 clinical medicineRobustness (computer science)Stress (linguistics)[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringmedicine[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Facial expression[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]anxietyimage processingRecognition[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][SPI.OPTI]Engineering Sciences [physics]/Optics / PhotonicAnxiety020201 artificial intelligence & image processing[ SPI.OPTI ] Engineering Sciences [physics]/Optics / Photonicmedicine.symptom030217 neurology & neurosurgery
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Maximum likelihood difference scaling of image quality in compression-degraded images.

2007

International audience; Lossy image compression techniques allow arbitrarily high compression rates but at the price of poor image quality. We applied maximum likelihood difference scaling to evaluate image quality of nine images, each compressed via vector quantization to ten different levels, within two different color spaces, RGB and CIE 1976 L(*)a(*)b(*). In L(*)a(*)b(*) space, images could be compressed on average by 32% more than in RGB space, with little additional loss in quality. Further compression led to marked perceptual changes. Our approach permits a rapid, direct measurement of the consequences of image compression for human observers.

[ INFO ] Computer Science [cs]Image qualityColorImage processing[INFO] Computer Science [cs]Color space050105 experimental psychology03 medical and health sciences0302 clinical medicineOpticsImage Processing Computer-Assisted[INFO]Computer Science [cs]0501 psychology and cognitive sciences[SDV.MHEP.OS]Life Sciences [q-bio]/Human health and pathology/Sensory OrgansImage resolutionMathematicsColor imagebusiness.industry05 social sciencesVector quantizationData CompressionAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic Materials[SDV.MHEP.OS] Life Sciences [q-bio]/Human health and pathology/Sensory Organs[ SDV.MHEP.OS ] Life Sciences [q-bio]/Human health and pathology/Sensory OrgansRGB color modelComputer Vision and Pattern RecognitionArtifactsbusiness030217 neurology & neurosurgeryImage compression
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Cardiac motion tracking using a deformable 2D-mesh modeling

2001

International audience; Abstract: The work reported here deals with movement tracking in sequences of medical images in order to quantify the general movements and deformations of the heart For this purpose, we partition the first image into triangular patches in order that each object of the image corresponds to a set of triangles. Then, the nodes of the mesh are tracked across the image sequence giving a mesh which warps with the images. The method is applied to cardiac image sequences where the study of the deformation of the triangles is applied to the determination of the movement of the ventricles

[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingMovement (music)business.industryComputer sciencePhysics::Medical Physics[INFO.INFO-IM] Computer Science [cs]/Medical ImagingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyImage segmentationDeformation (meteorology)Tracking (particle physics)030218 nuclear medicine & medical imagingImage (mathematics)Set (abstract data type)03 medical and health sciences0302 clinical medicineComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineeringMedical imaging[INFO.INFO-IM]Computer Science [cs]/Medical Imaging020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessComputingMethodologies_COMPUTERGRAPHICS
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OPTIMIZATIONS FOR TENSORIAL BERNSTEIN–BASED SOLVERS BY USING POLYHEDRAL BOUNDS

2010

The tensorial Bernstein basis for multivariate polynomials in n variables has a number 3n of functions for degree 2. Consequently, computing the representation of a multivariate polynomial in the tensorial Bernstein basis is an exponential time algorithm, which makes tensorial Bernstein-based solvers impractical for systems with more than n = 6 or 7 variables. This article describes a polytope (Bernstein polytope) with a number of faces, which allows to bound a sparse, multivariate polynomial expressed in the canonical basis by solving several linear programming problems. We compare the performance of a subdivision solver using domain reductions by linear programming with a solver using a c…

[ INFO.INFO-NA ] Computer Science [cs]/Numerical Analysis [cs.NA]Linear programmingPolytopeBernstein polynomials01 natural sciencesSimplex algorithmApplied mathematicssimplex algorithm0101 mathematicsMathematicsDiscrete mathematicsBasis (linear algebra)Applied Mathematics010102 general mathematicssubdivision solverlinear programmingalgebraic systemsQuadratic function[INFO.INFO-NA]Computer Science [cs]/Numerical Analysis [cs.NA]Solver1991 Mathematics Subject Classification: 14Q15 14Q20 65G40Bernstein polynomialComputer Science Applications010101 applied mathematicsModeling and SimulationStandard basisGeometry and TopologyComputer Vision and Pattern RecognitionSoftwareInternational Journal of Shape Modeling
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Comparison of Bathymetric estimation using different satellite images in coastal sea waters

2009

Bathymetric estimation can be obtained from multispectral satellite images for shallow waters. The method is based on the rotation of a pair of spectral bands. One of the resulting images is depth-dependent. Therefore several pixels corresponding to different depths are required to numerically evaluate the linear relation between the pixel values and the real depth for a training area. The aim of this study is to compare, for one bathymetric estimation method and one mesotrophic site, the results of depth estimation with a large panel of satellite and aerial images: CASI, QUICKBIRD, CHRIS PROBA, ETM, HYPERION and MeRIS. For each image the pair of spectral bands chosen to compute the bathyme…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciencesPixelAerial survey[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMultispectral image0211 other engineering and technologies02 engineering and technologySpectral bands01 natural sciencesMultispectral pattern recognition[SPI]Engineering Sciences [physics][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer Science::Computer Vision and Pattern RecognitionGeneral Earth and Planetary SciencesBathymetry14. Life underwaterQuantization (image processing)Image resolution[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingGeologyComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Multispectral Imaging using a Stereo Camera: Concept, Design and Assessment

2011

This paper proposes a one-shot six-channel multispectral color image acquisition system using a stereo camera and a pair of optical filters. The two filters from the best pair selected from among readily available filters such that they modify the sensitivities of the two cameras in such a way that they produce optimal estimation of spectral reflectance and/or color are placed in front of the two lenses of the stereo camera. The two images acquired from the stereo camera are then registered for pixel-to-pixel correspondence. The spectral reflectance and/or color at each pixel on the scene are estimated from the corresponding camera outputs in the two images. Both simulations and experiments…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONlcsh:TK7800-836002 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural scienceslcsh:Telecommunicationlaw.inventionMultispectral pattern recognitionstereo camera010309 optics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessinglawCamera auto-calibrationlcsh:TK5101-67200103 physical sciences0202 electrical engineering electronic engineering information engineeringmultispectral imagingComputer visionreflectance estimationPixelColor imagebusiness.industrylcsh:ElectronicsReflectivityLens (optics)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing:Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 [VDP]Stereo cameraComputer stereo visionCamera resectioning
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Reaction-Diffusion Network For Geometric Multiscale High Speed Image Processing

2010

International audience; In the framework of heavy mid-level processing for high speed imaging, a nonlinear bi-dimensional network is proposed, allowing the implementation of active curve algorithms. Usually this efficient type of algorithm is prohibitive for real-time image processing due to its calculus charge and the inadequate structure for the use of serial or parallel architectures. Another kind of implementation philosophy is proposed here, by considering the active curve generated by a propagation phenomenon inspired from biological modeling. A programmable nonlinear reaction-diffusion system is proposed under front control and technological constraints. Geometric multiscale processin…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceNonlinear signal processingImage processing02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingType (model theory)Multiscale geometryComputational scienceImage analysisNonlinear signal processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingReaction–diffusion systemDigital image processing0202 electrical engineering electronic engineering information engineeringComputer visionStructure (mathematical logic)Biological modelingbusiness.industry020208 electrical & electronic engineeringNonlinear systemSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Spatially variant dimensionality reduction for the visualization of multi/hyperspectral images

2011

International audience; In this paper, we introduce a new approach for color visu- alization of multi/hyperspectral images. Unlike traditional methods, we propose to operate a local analysis instead of considering that all the pixels are part of the same population. It takes a segmentation map as an input and then achieves a dimensionality reduction adaptively inside each class of pixels. Moreover, in order to avoid unappealing discon- tinuities between regions, we propose to make use of a set of distance transform maps to weigh the mapping applied to each pixel with regard to its relative location with classes' centroids. Results on two hyperspec- tral datasets illustrate the efficiency of…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencePopulation0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionSegmentationspectral imageseducationspatially variantvisualization021101 geological & geomatics engineeringdimensionality reductioneducation.field_of_studyPixelbusiness.industryDimensionality reductionHyperspectral imagingIndependent component analysisVisualizationComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingArtificial intelligencebusinessDistance transform[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Validation of a 2D multispectral camera: application to dermatology/cosmetology on a population covering five skin phototypes

2011

International audience; This paper presents the validation of a new multispectral camera specifically developed for dermatological application based on healthy participants from five different Skin PhotoTypes (SPT). The multispectral system provides images of the skin reflectance at different spectral bands, coupled with a neural network-based algorithm that reconstructs a hyperspectral cube of cutaneous data from a multispectral image. The flexibility of neural network based algorithm allows reconstruction at different wave ranges. The hyperspectral cube provides both high spectral and spatial information. The study population involves 150 healthy participants. The participants are classif…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer sciencePopulationMultispectral imageSkin imaging system[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingspectral reflectance01 natural sciencesspectral reconstructionMultispectral pattern recognition010309 optics030207 dermatology & venereal diseases03 medical and health sciencesFitzpatrick scale0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical scienceseducationRemote sensingvalidationeducation.field_of_studyHyperspectral imagingSpectral bandshyperspectral cubemultispectral imageFace (geometry)Cube[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A nonlinear oscillators network devoted to image processing

2004

A contrast enhancement and image inverting tool using a lattice of uncoupled nonlinear oscillators is proposed. We show theoretically and numerically that the gray scale picture contrast is strongly enhanced even if this one is initially very small. An image inversion can be also obtained in real time with the same Cellular Nonlinear Network (CNN) without reconfiguration of the network. A possible electronic implementation of this CNN is finally discussed.

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[ PHYS.COND.CM-DS-NN ] Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]Image processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCellular nonlinear networksTopology01 natural sciencesGrayscale010305 fluids & plasmasNonlinear oscillators[NLIN.NLIN-PS]Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingControl theoryLattice (order)0103 physical sciences[ NLIN.NLIN-PS ] Nonlinear Sciences [physics]/Pattern Formation and Solitons [nlin.PS][PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]010306 general physicsEngineering (miscellaneous)ComputingMilieux_MISCELLANEOUSArtificial neural networkApplied MathematicsControl reconfigurationInversion (meteorology)neural networks[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsNonlinear systemComputer Science::Computer Vision and Pattern RecognitionModeling and SimulationNonlinear dynamics[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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