Search results for "Visual System"

showing 10 items of 60 documents

Retinal ganglion cells projecting to the optic tectum and visual thalamus of lizards.

2002

Retinal ganglion cells projecting to the optic tectum and visual thalamus have been investigated in the lizard, Podarcis hispanica. Injections of biotinylated dextran-amine in the optic tectum reveal seven morphological cell varieties including one displaced ganglion cell type. Injections in the visual thalamus yield similar ganglion cell classes plus four giant ganglion cells, including two displaced ganglion cell types. The present study constitutes the first comparison of tectal versus thalamic ganglion cell types in reptiles. The situation found in lizards is similar to that reported in mammals and birds where some cell types projecting to the thalamus are larger than those projecting t…

Retinal Ganglion CellsRetinaSuperior ColliculiPhysiologyBistratified cellGiant retinal ganglion cellsLizardsAnatomyVisual systemBiologyInner plexiform layerRetinal ganglionSynaptic TransmissionSensory SystemsParasol cellGanglionmedicine.anatomical_structurenervous systemThalamusmedicineAnimalsVisual Pathwayssense organsNeuroscienceCell SizeVisual neuroscience
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Seeing with the visual cortex

1984

A short analysis of the input-output organization of the primary visual cortical areas in the cat and monkey is followed by a description of the salient microelectrophysiological properties of retino-geniculo-cortical system neurons. It is concluded that a strict hierarchical model of cortical processing of visual information is no longer tenable.

Retinal Ganglion Cellsgenetic structuresMotion PerceptionDermatologyVisual systemCortical processingmedicineAnimalsVisual PathwaysBinocular neuronsVisual CortexBrain MappingOrientation columnGeneral NeuroscienceGeniculate BodiesHaplorhiniGeneral MedicineForm PerceptionPsychiatry and Mental healthVisual cortexmedicine.anatomical_structureSalientSynapsesCatsVisual PerceptionNeurology (clinical)Visual FieldsPsychologyNeuroscienceThe Italian Journal of Neurological Sciences
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Midground Object Detection in Real World Video Scenes,

2007

Traditional video scene analysis depends on accurate background modeling to identify salient foreground objects. However, in many important surveillance applications, saliency is defined by the appearance of a new non-ephemeral object that is between the foreground and background. This midground realm is defined by a temporal window following the object's appearance; but it also depends on adaptive background modeling to allow detection with scene variations (e.g., occlusion, small illumination changes). The human visual system is ill-suited for midground detection. For example, when surveying a busy airline terminal, it is difficult (but important) to detect an unattended bag which appears…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScene statisticsObject (computer science)Object detectionObject-class detectionComputational efficiencyComputer networksSalientVideo trackingHuman visual system modelComputer visionViola–Jones object detection frameworkArtificial intelligencebusiness
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Adaptive motion estimation and video vector quantization based on spatiotemporal non-linearities of human perception

1997

The two main tasks of a video coding system are motion estimation and vector quantization of the signal. In this work a new splitting criterion to control the adaptive decomposition for the non-uniform optical flow estimation is exposed. Also, a novel bit allocation procedure is proposed for the quantization of the DCT transform of the video signal. These new approaches are founded on a perception model that reproduce the relative importance given by the human visual system to any location in the spatial frequency, temporal frequency and amplitude domain of the DCT transform. The experiments show that the proposed procedures behave better than their equivalent (fixed-block-size motion estim…

Signal processingAdaptive algorithmComputer sciencebusiness.industryTrellis quantizationQuantization (signal processing)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVector quantizationIterative reconstructionOptical flow estimationMotion estimationComputer Science::MultimediaHuman visual system modelDiscrete cosine transformComputer visionArtificial intelligencebusinessQuantization (image processing)
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3D objects descriptors methods: Overview and trends

2017

International audience; Object recognition or object's category recognition under varying conditions is one of the most astonishing capabilities of human visual system. The scientists in computer vision have been trying for decades to reproduce this ability by implementing algorithms and providing computers with appropriate tools. Hence, several intelligent systems have been proposed. To act in this field, numerous approaches have been proposed. In this paper we present an overview of the current trend in 3D objects recognition and describe some representative state of the art methods, highlighting their limits and complexity.

Sketch recognitionComputer science3D single-object recognition[INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR]02 engineering and technology[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]Field (computer science)object recognitionhuman visual systemcomputer vision[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingHuman–computer interactionobject category recognition0202 electrical engineering electronic engineering information engineeringskeletonComputer vision3D objects descriptors methodsVisualization3D objects recognitionintelligent systemsNon-Controlled Indexingbusiness.industryCognitive neuroscience of visual object recognitionIntelligent decision support system[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Shape020207 software engineeringComputational modelingObject (computer science)Keypoints3D objects[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]VisualizationRecognition[INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG]Human visual system modelSolid modelingThree-dimensional displays020201 artificial intelligence & image processingArtificial intelligencebusiness
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Panel Summary One Model for Vision Systems?

1994

This panel reports some considerations about the definition of vision-models. The panellists are scientists working on vision problems from different perspectives. The concept of model in vision seems to remain still open. In fact, it is dynamic, and context dependent. There exists the need for a better exchange of information, among biologists, engineers, physicists, and psychologists in order to improve our knowledge.

StereopsisExchange of informationMachine visionComputer scienceOrder (business)Human–computer interactionExistential quantificationHuman visual system modelContext (language use)
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Biologically Inspired Model for Inference of 3D Shape from Texture.

2015

A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can…

Surface (mathematics)PhysiologyVisual SystemVisionComputer scienceSensory PhysiologySocial Scienceslcsh:Medicine0302 clinical medicineAnimal CellsMedicine and Health SciencesPsychologylcsh:ScienceVisual CortexNeuronsMultidisciplinaryOrientation (computer vision)Physics05 social sciencesBrainCondensed Matter PhysicsSensory SystemsSignal FilteringPhysical SciencesVisual PerceptionEngineering and TechnologySensory PerceptionAnatomyCellular TypesAlgorithmsResearch ArticleSurface PropertiesMaterials ScienceMaterial PropertiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeometryModels BiologicalTexture (geology)050105 experimental psychology03 medical and health sciencesHumansVisual Pathways0501 psychology and cognitive sciencesRepresentation (mathematics)ComputingMethodologies_COMPUTERGRAPHICSCurvaturebusiness.industrylcsh:RBiology and Life SciencesPattern recognitionCell BiologyObject (computer science)Form PerceptionCellular NeuroscienceSignal ProcessingAnisotropylcsh:QArtificial intelligencebusinessMathematics030217 neurology & neurosurgeryNeurosciencePLoS ONE
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On the classification of visual patterns: systems analysis using detection experiments.

1977

Behavioral experiments are indispensable for the analysis of biological systems for cognition and recognition. When these are carried out as detection experiments three types of description can be used for the problem of visual pattern recognition which allow conclusions to be drawn on the operating function of the system. Provided that the signals to be recognized have additive noise superimposed on them, system description is possible: 1. on the basis on the probabilities of recognition and of mix-up,--2. through the analysis of the transformation of distribution densities of the noise,--3. by means of the measurable distances of the patterns from each other in feature space.-The analysis…

Systems AnalysisGeneral Computer ScienceBasis (linear algebra)business.industryComputersSpectral densityLinear classifierPattern recognitionClassificationForm PerceptionNoiseTransformation (function)Pattern Recognition VisualHuman visual system modelFeature (machine learning)HumansArtificial intelligencebusinessIndependence (probability theory)MathematicsBiotechnologyMathematicsBiological cybernetics
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Sensory system interactions during simultaneous vestibular and visual stimulation in PET

2002

The patterns of regional cerebral blood flow (rCBF) increases and decreases in PET were compared for unimodal vestibular, unimodal visual, and for simultaneous vestibular and visual stimulation. Thirteen healthy volunteers were exposed to a) caloric vestibular stimulation, b) small-field visual motion stimulation in roll, c) simultaneous caloric vestibular and visual pattern stimulation. Unimodal vestibular stimulation led to activations of vestibular cortex areas, in particular the parieto-insular vestibular cortex (PIVC), and concurrent deactivations of visual cortical areas [Brodmann area (BA) 17-19]. Unimodal visual motion stimulation led to activations of the striate visual cortex and …

Vestibular systemgenetic structuresRadiological and Ultrasound TechnologyPhotic StimulationSensory systemVisual systemVestibular cortexVisual cortexmedicine.anatomical_structureNeurologyotorhinolaryngologic diseasesmedicineRadiology Nuclear Medicine and imagingsense organsNeurology (clinical)Motion perceptionAnatomyPsychologyNeuroscienceBrodmann areaHuman Brain Mapping
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<title>Computerized device for critical flicker fusion frequency determination</title>

2003

The critical fusion flicker frequency of the human visual system is the threshold sensitivity for a sine wave-modulated patch of monochromatic flickering light measured as a function of its temporal frequency and average luminance level. The critical flicker fusion frequency changes in different ocular and non-ocular conditions, for example: high-myopia, AMR, glaucoma, schizophrenia, after alcohol intake, fatigue. A computerized test for critical flicker fusion frequency determination was developed. Visual stimuli are two monochromatic LED light sources that are connected to a microcircuit driven by a computer program. The control of the device is realized through the parallel port of the P…

Visual perceptiongenetic structuresComputer sciencebusiness.industryFlickerFlicker fusion thresholdLuminanceeye diseaseslaw.inventionLED lampOpticslawHuman visual system modelMonochromatic colorbusinessSensitivity (electronics)SPIE Proceedings
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