Search results for "Motion detection"

showing 10 items of 25 documents

Small field motion detection in goldfish is red-green color blind and mediated by the M-cone type

2007

Large field motion detection in goldfish, measured in the optomotor response, is based on the L-cone type, and is therefore color-blind (Schaerer & Neumeyer, 1996). In experiments using a two-choice training procedure, we investigated now whether the same holds for the detection of a small moving object (size: 8 mm diameter; velocity: 7 cm/s). In initial experiments, we found that goldfish did not discriminate between a moving and a stationary stimulus, obviously not taking attention to the cue “moving.” Therefore, random dot patterns were used in which the stimulus was visible only when moving. Using black and white random dot patterns with variable contrast between 0.2 and 1, we found…

PhysicsCommunicationBehavior AnimalAdaptation OcularPhysiologybusiness.industryColor visionMotion PerceptionMotion detectionObject motionStimulus (physiology)Choice BehaviorSensory SystemsSmall fieldOpticsGreen colorGoldfishRetinal Cone Photoreceptor CellsOptomotor responseAnimalsbusinessColor PerceptionPhotic StimulationExcitationVisual Neuroscience
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2013

The motion energy sensor has been shown to account for a wide range of physiological and psychophysical results in motion detection and discrimination studies. It has become established as the standard computational model for retinal movement sensing in the human visual system. Adaptation effects have been extensively studied in the psychophysical literature on motion perception, and play a crucial role in theoretical debates, but the current implementation of the energy sensor does not provide directly for modelling adaptation-induced changes in output. We describe an extension of the model to incorporate changes in output due to adaptation. The extended model first computes a space-time r…

PhysicsMultidisciplinary05 social sciencesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONLeaky integratorMotion detection050105 experimental psychologylaw.invention03 medical and health sciences0302 clinical medicineExtended modelControl theorylawElectrical networkHuman visual system modelPsychophysics0501 psychology and cognitive sciencesMotion perceptionResistor030217 neurology & neurosurgeryPLOS ONE
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The physiological basis for the computation of direction selectivity in theDrosophilaOFF pathway

2021

AbstractInDrosophila, direction-selective neurons implement a mechanism of motion computation similar to cortical neurons, using contrast-opponent receptive fields with ON and OFF subunits. It is not clear how the presynaptic circuitry of direction-selective neurons in the OFF pathway supports this computation, because all major inputs are OFF-rectified neurons. Here, we reveal the biological substrate for motion computation in the OFF pathway. Three interneurons, Tm2, Tm9 and CT1, also provide information about ON stimuli to the OFF direction-selective neuron T5 across its receptive field, supporting a contrast-opponent receptive field organization. Consistent with its prominent role in mo…

Physicsmedicine.anatomical_structureBasis (linear algebra)Off pathwayReceptive fieldComputationmedicineMotion detectionCortical neuronsNeuronNeuroscienceMotion computation
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Speeding-Up Differential Motion Detection Algorithms Using a Change-Driven Data Flow Processing Strategy

2007

A constraint of real-time implementation of differential motion detection algorithms is the large amount of data to be processed. Full image processing is usually the classical approach for these algorithms: spatial and temporal derivatives are calculated for all pixels in the image despite the fact that the majority of image pixels may not have changed from one frame to the next. By contrast, the data flow model works in a totally different way as instructions are only fired when the data needed for these instructions are available. Here we present a method to speed-up low level motion detection algorithms. This method is based on pixel change instead of full image processing and good spee…

PixelComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingMotion detectionData flow diagramMotion fieldComputer Science::Computer Vision and Pattern RecognitionMotion estimationDigital image processingComputer visionArtificial intelligencebusinessAlgorithmFeature detection (computer vision)
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Selective Change Driven Vision Sensor With Continuous-Time Logarithmic Photoreceptor and Winner-Take-All Circuit for Pixel Selection

2015

The objective of Selective Change Driven (SCD) Vision is to capture and process those scene pixels that have the greatest impact in the motion estimation task. The implemented SCD Vision sensor delivers the pixels ordered according to the illumination change undergone by each pixel, from the last time each pixel was read-out. This ordering strategy is especially interesting for motion detection algorithms, since it allows for a reduction in data bandwidth requirements without decreasing accuracy. The speed of the obtained pixel flow allows movement detection and tracking at a speed several orders of magnitude higher than conventional vision systems. To accomplish these objectives, the senso…

PixelLogarithmComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Motion detectionReduction (complexity)Orders of magnitude (time)Motion estimationComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessIEEE Journal of Solid-State Circuits
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Selective Change-Driven Image Processing: A Speeding-Up Strategy

2009

Biologically inspired schemes are a source for the improvement of visual systems. Real-time implementation of image processing algorithms is constrained by the large amount of data to be processed. Full image processing is many times unnecessary since there are many pixels that suffer a small change or not suffer any change at all. A strategy based on delivering and processing pixels, instead of processing the complete frame, is presented. The pixels that have suffered higher changes in each frame, ordered by the absolute value of its change, are read-out and processed. Two examples are shown: a morphological motion detection algorithm and the Horn and Schunck optical flow algorithm. Result…

Pixelbusiness.industryComputer scienceFrame (networking)Digital image processingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowMotion detectionComputer visionImage processingAbsolute valueArtificial intelligencebusiness
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Cloud motion detection from infrared satellite images

2002

The estimation of cloud motion from a sequence of satellite images can be considered a challenging task due to the complexity of phenomena implied. Being a non-rigid motion and implying non-linear events, most motion models are not suitable and new algorithms have to be developed. We propose a novel technique, combining a Block Matching Algorithm (BMA) and a best candidate block search along with a vector median regularisation.

SequenceComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMotion detectionCloud computingMotion (physics)Jump searchMotion estimationSatelliteComputer visionArtificial intelligencebusinessBlock-matching algorithmSPIE Proceedings
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Real-time estimation of geometrical transformation between views in distributed smart-cameras systems

2008

In this paper, we present a method to automatically estimate the geometric relations among the different views of cameras with partially overlapping fields of view in a wireless video-surveillance system. The method uses the locations of the detected moving objects visible at the same time in two or more views. The correspondences among objects are found by comparing their appearance models based on dominant colour descriptors while the geometric transformation are computed iteratively and may be used to solve the consistent labelling problem. As a significant part of the processing is performed on the smart cameras, the method has been conceived by taking into account the limited resources…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryGeometric transformationMotion detectiondistributed video surveillanceObject detectionData modelingTransformation (function)Computer visionSmart cameraArtificial intelligenceImage sensorbusinessHomography (computer vision)2008 Second ACM/IEEE International Conference on Distributed Smart Cameras
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Sight sublimated by odors: effect of subliminal odors on facial emotion detection.

2014

SightOphthalmologyCommunicationbusiness.industryEmotion detectionSubliminal stimulibusinessPsychologySensory SystemsJournal of Vision
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The physiological basis for contrast opponency in motion computation in Drosophila

2021

This dataset contains traces (dF/F0) from in vivo two-photon calcium imaging from Tm1, tm2, Tm4, Tm9, CT1, and T5 neurons from responses to ONOFF fullfield flashes, ON and OFF bars, and moving sinewaves.

Vision modelsMotion detectionDirection selectivityCalcium imagingContrast opponencyDirection selectivity modelsReceptive fieldDrosophila vision
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