Search results for "Visual System"

showing 10 items of 60 documents

Non-linear Invertible Representation for Joint Statistical and Perceptual Feature Decorrelation

2000

The aim of many image mappings is representing the signal in a basis of decorrelated features. Two fundamental aspects must be taken into account in the basis selection problem: data distribution and the qualitative meaning of the underlying space. The classical PCA techniques reduce the statistical correlation using the data distribution. However, in applications where human vision has to be taken into account, there are perceptual factors that make the feature space uneven, and additional interaction among the dimensions may arise. In this work a common framework is presented to analyse the perceptual and statistical interactions among the coefficients of any representation. Using a recen…

Computer sciencebusiness.industryFeature vectormedia_common.quotation_subjectComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionlaw.inventionLinear mapNonlinear systemInvertible matrixlawPerceptionHuman visual system modelArtificial intelligencebusinessDecorrelationmedia_common
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Analyse des Visuellen Klassifikationssystems Durch Detektionsexperimente

1977

Summary Experiments on recognizing statistically distorted patterns show that the human visual system operates as a linear classifier. The spatial frequency range, within which features are extracted, is determined by the coupling in the area of sharpest vision (2°). The relevant features for classifying patterns are not produced by isotropic filtering

Computer sciencebusiness.industrySpeech recognitionHuman visual system modelPattern recognitionLinear classifierSpatial frequencyArtificial intelligencebusinessIFAC Proceedings Volumes
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Mesh Visual Quality Assessment Metrics: A Comparison Study

2017

3D graphics technologies have known a developed progress in the last years, and several processing operations can be applied on 3D meshes such as watermarking, compression, simplification and so forth. Mesh visual quality assessment becomes an important issue to evaluate the visual appearance of the 3D shape after specific modifications. Several metrics have been proposed in this context, from the classical distance-based metrics to the perceptual-based metrics which include perceptual information about the human visual system. In this paper, we propose to study the performance of several mesh visual quality metrics. First, the comparison is conducted regardless the distortion types neither…

Computer sciencemedia_common.quotation_subject020207 software engineeringContext (language use)02 engineering and technologycomputer.software_genreVisual appearanceVisualizationMetric (mathematics)Human visual system model0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingQuality (business)Polygon meshData miningcomputer3D computer graphicsmedia_common2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
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Color illusions also deceive CNNs for low-level vision tasks: Analysis and implications.

2019

The study of visual illusions has proven to be a very useful approach in vision science. In this work we start by showing that, while convolutional neural networks (CNNs) trained for low-level visual tasks in natural images may be deceived by brightness and color illusions, some network illusions can be inconsistent with the perception of humans. Next, we analyze where these similarities and differences may come from. On one hand, the proposed linear eigenanalysis explains the overall similarities: in simple CNNs trained for tasks like denoising or deblurring, the linear version of the network has center-surround receptive fields, and global transfer functions are very similar to the human …

Computer sciencemedia_common.quotation_subjectIllusionColor spaceConvolutional neural network050105 experimental psychology03 medical and health sciences0302 clinical medicinePerceptionHumans0501 psychology and cognitive sciencesVision Ocularmedia_commonArtificial neural networkbusiness.industryOptical illusion05 social sciencesIllusionsSensory SystemsOphthalmologyVision scienceHuman visual system modelArtificial intelligenceNeural Networks Computerbusiness030217 neurology & neurosurgeryVision research
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Perceptually Optimized Image Rendering

2017

We develop a framework for rendering photographic images by directly optimizing their perceptual similarity to the original visual scene. Specifically, over the set of all images that can be rendered on a given display, we minimize the normalized Laplacian pyramid distance (NLPD), a measure of perceptual dissimilarity that is derived from a simple model of the early stages of the human visual system. When rendering images acquired with a higher dynamic range than that of the display, we find that the optimization boosts the contrast of low-contrast features without introducing significant artifacts, yielding results of comparable visual quality to current state-of-the-art methods, but witho…

FOS: Computer and information sciencesComputer Science - Artificial IntelligenceImage qualityComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologyLuminanceRendering (computer graphics)Computer Science - GraphicsOptics0202 electrical engineering electronic engineering information engineeringComputer visionPower functionComputingMethodologies_COMPUTERGRAPHICSbusiness.industryDynamic range020207 software engineeringAtomic and Molecular Physics and OpticsGraphics (cs.GR)Electronic Optical and Magnetic MaterialsArtificial Intelligence (cs.AI)Human visual system model020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessImage compression
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PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance

2019

Traditionally, the vision community has devised algorithms to estimate the distance between an original image and images that have been subject to perturbations. Inspiration was usually taken from the human visual perceptual system and how the system processes different perturbations in order to replicate to what extent it determines our ability to judge image quality. While recent works have presented deep neural networks trained to predict human perceptual quality, very few borrow any intuitions from the human visual system. To address this, we present PerceptNet, a convolutional neural network where the architecture has been chosen to reflect the structure and various stages in the human…

FOS: Computer and information sciencesComputer Science - Machine LearningVisual perceptionComputer scienceImage qualitymedia_common.quotation_subjectFeature extractionMachine Learning (stat.ML)02 engineering and technology01 natural sciencesConvolutional neural networkhuman visual systemMachine Learning (cs.LG)010309 opticsStatistics - Machine LearningPerception0103 physical sciences0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringperceptual distancemedia_commonArtificial neural networkbusiness.industryDeep learningImage and Video Processing (eess.IV)Pattern recognitionElectrical Engineering and Systems Science - Image and Video Processingneural networksHuman visual system model020201 artificial intelligence & image processingArtificial intelligencebusiness
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Subjective image fidelity metric based on bit allocation of the human visual system in the DCT domain

1997

Until now, subjective image distortion measures have partially used diverse empirical facts concerning human perception: non-linear perception of luminance, masking of the impairments by a highly textured surround, linear filtering by the threshold contrast frequency response of the visual system, and non-linear post-filtering amplitude corrections in the frequency domain. In this work, we develop a frequency and contrast dependent metric in the DCT domain using a fully non-linear and suprathreshold contrast perception model: the Information Allocation Function (IAF) of the visual system. It is derived from experimental data about frequency and contrast incremental thresholds and it is cons…

Frequency responsegenetic structuresImage qualitybusiness.industrymedia_common.quotation_subjectDistortionFrequency domainSignal ProcessingMetric (mathematics)Human visual system modelContrast (vision)Computer visionComputer Vision and Pattern RecognitionArtificial intelligencebusinessData compressionmedia_commonMathematics
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Reduced reference 3D mesh quality assessment based on statistical models

2015

International audience; During their geometry processing and transmission 3D meshes are subject to various visual processing operations like compression, watermarking, remeshing, noise addition and so forth. In this context it is indispensable to evaluate the quality of the distorted mesh, we talk here about the mesh visual quality (MVQ) assessment. Several works have tried to evaluate the MVQ using simple geometric measures, However this metrics do not correlate well with the subjective score since they fail to reflect the perceived quality. In this paper we propose a new objective metric to evaluate the visual quality between a mesh with a perfect quality called reference mesh and its dis…

Gamma distribution[ INFO ] Computer Science [cs]Kullback–Leibler divergenceKullback-Leibler divergencestatistical modelingContext (language use)02 engineering and technologyhuman visual systemDatabases[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringcomputational geometryPolygon mesh[INFO]Computer Science [cs]Divergence (statistics)MathematicsComputingMethodologies_COMPUTERGRAPHICSVisualizationbusiness.industry020207 software engineeringStatistical modelPattern recognitionstatistical distributionsDistortionGeometry processing3D triangle mesh[ SPI.TRON ] Engineering Sciences [physics]/Electronicsimage processing[SPI.TRON]Engineering Sciences [physics]/ElectronicsHuman visual system modelMetric (mathematics)Solid modelingThree-dimensional displays020201 artificial intelligence & image processingDistortion measurementWeibull distributionArtificial intelligencebusinessobjective metricQuality assessment
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No-Reference 3D Mesh Quality Assessment Based on Dihedral Angles Model and Support Vector Regression

2016

International audience; 3D meshes are subject to various visual distortions during their transmission and geometrical processing. Several works have tried to evaluate the visual quality using either full reference or reduced reference approaches. However, these approaches require the presence of the reference mesh which is not available in such practical situations. In this paper, the main contribution lies in the design of a computational method to automatically predict the perceived mesh quality without reference and without knowing beforehand the distortion type. Following the no-reference (NR) quality assessment principle, the proposed method focuses only on the distorted mesh. Specific…

Gamma distribution[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[ INFO ] Computer Science [cs]Computer science02 engineering and technologycomputer.software_genre[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Quality (physics)[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingVisual maskingDistortion0202 electrical engineering electronic engineering information engineeringGamma distribution[INFO]Computer Science [cs]Polygon mesh[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]No-reference mesh quality assessmentVisual masking effect020207 software engineeringSupport vector machineSupport vector regressionQuality ScoreHuman visual system modelDihedral angles020201 artificial intelligence & image processingData miningAlgorithmcomputer
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An overall description of retinotopic mapping in the cat's visual cortex areas 17, 18, and 19.

1985

Mathematical functions are derived which model the retinotopic mapping in the cat's visual cortical areas 17, 18, and 19. All three mappings are simple modifications of a complex power function with an exponent of 0.43. This function is decomposed so as to give an intermediate stage which is common to all three mappings and can be regarded as a model of the lateral geniculate nucleus mapping. The influence of retinotopic mapping on visual receptive fields was studied. The results show that a dependence of the receptive field properties on the position in the visual field is to be expected.

General Computer ScienceModels NeurologicalVisual systemLateral geniculate nucleusRetinaPosition (vector)medicineAnimalsVisual CortexOrientation columnbusiness.industryPattern recognitionFunction (mathematics)Visual fieldVisual cortexmedicine.anatomical_structureReceptive fieldCatsVisual PerceptionArtificial intelligenceVisual FieldsbusinessPsychologyNeuroscienceMathematicsSoftwareBiotechnologyBiological cybernetics
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