Search results for "VISION"

showing 10 items of 5066 documents

A novel Bayesian framework for relevance feedback in image content-based retrieval systems

2006

This paper presents a new algorithm for image retrieval in content-based image retrieval systems. The objective of these systems is to get the images which are as similar as possible to a user query from those contained in the global image database without using textual annotations attached to the images. The main problem in obtaining a robust and effective retrieval is the gap between the low level descriptors that can be automatically extracted from the images and the user intention. The algorithm proposed here to address this problem is based on the modeling of user preferences as a probability distribution on the image space. Following a Bayesian methodology, this distribution is the pr…

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONRelevance feedbackPattern recognitioncomputer.software_genreAutomatic image annotationArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingProbability distributionComputer Vision and Pattern RecognitionVisual WordArtificial intelligenceData miningbusinessPrecision and recallImage retrievalcomputerSoftwarePattern Recognition
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Robust Hand Gestures Recognition Using a Deep CNN and Thermal Images

2021

Medical systems and assistive technologies, human-computer interaction, human-robot interaction, industrial automation, virtual environment control, sign language translation, crisis and disaster management, entertainment and computer games, and so on all use RGB cameras for hand gesture recognition. However, their performance is limited especially in low-light conditions. In this paper, we propose a robust hand gesture recognition system based on high-resolution thermal imaging that is light-independent. A dataset of 14,400 thermal hand gestures is constructed, separated into two color tones. We also propose using a deep CNN to classify high-resolution hand gestures accurately. The propose…

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSign languagecomputer.software_genreAutomationVirtual machineGesture recognitionBenchmark (computing)RGB color modelComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessInstrumentationcomputerEdge computingGestureIEEE Sensors Journal
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Real-time people counting system using a single video camera

2008

This is the copy of journal's version originally published in Proc. SPIE 6811. Reprinted with permission of SPIE: http://spie.org/x10.xml?WT.svl=tn7 There is growing interest in video-based solutions for people monitoring and counting in business and security applications. Compared to classic sensor-based solutions the video-based ones allow for more versatile functionalities, improved performance with lower costs. In this paper, we propose a real-time system for people counting based on single low-end non-calibrated video camera. The two main challenges addressed in this paper are: robust estimation of the scene background and the number of real persons in merge-split scenarios. The latter…

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVideo cameraImage processingKalman filterThresholdinglaw.inventionAdaptive filterlawVideo trackingSegmentationComputer visionArtificial intelligencebusiness:Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 [VDP]Block-matching algorithm
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Efficient Skin Detection under Severe Illumination Changes and Shadows

2011

International audience; This paper presents an efficient method for human skin color detection with a mobile platform. The proposed method is based on modeling the skin distribution in a log-chromaticity color space which shows good invariance properties to changing illumination. The method is easy to implement and can cope with the requirements of real-world tasks such as illumination variations, shadows and moving camera. Extensive experiments show the good performance of the proposed method and its robustness against abrupt changes of illumination and shadows.

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineering02 engineering and technologyFace detectionColor spaceInvariance to illumination[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Robustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceLog-chromaticity color spaceColor detectionbusinessFace detectionSkin detectionComputingMethodologies_COMPUTERGRAPHICS
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Quantitative Geometric Three-Dimensional Reconstruction of Neuronal Architecture and Mapping of Labeled Proteins from Confocal Image Stacks

2014

Computer sciencebusiness.industryConfocalComputer visionArtificial intelligenceArchitecturebusinessImage (mathematics)
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Comparison of Statistical Methods for the Detection of Contrast Material in Echocardiographic Image Sequences

1987

Ultrasonic imaging of the heart is a diagnostic tool which is increasingly used in cardiology. In addition to the representation of important anatomical information two dimensional images provided by mechanical or electronically steered sector scanners can be used for the extraction of functional parameters of the heart (as e.g. enddiastolic volume or ejection fraction). A poor definition of the endocardial border especially resulting from the noisy appearance of the images and from qualitatively restricted echocardiograms leads to uncertainties in the quantitative analysis and therefore requires refined methods for the determination of functional parameters. Our investigations which are ba…

Computer sciencebusiness.industryContrast (statistics)Ultrasonic sensorComputer visionPattern recognitionArtificial intelligenceRepresentation (mathematics)Endocardial borderbusinessEchocardiographic imageUltrasonic imaging
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A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites

2021

Aerial inspection of solar modules is becoming increasingly popular in automatizing operations and maintenance in large-scale photovoltaic power plants. Current practices are typically time-consuming as they make use of manual acquisitions and analysis of thousands of images to scan for faults and anomalies in the modules. In this paper, we explore and evaluate the use of computer vision and deep learning methods for automating the analysis of fault detection and classification in large scale photovoltaic module installations. We use convolutional neural networks to analyze thermal and visible color images acquired by cameras mounted on unmanned aerial vehicles. We generate composite images…

Computer sciencebusiness.industryDeep learningPhotovoltaic systemComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingFault (power engineering)Convolutional neural networkFault detection and isolationFeature (computer vision)HistogramComputer visionArtificial intelligencebusiness2021 IEEE 48th Photovoltaic Specialists Conference (PVSC)
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Hand Detection and Tracking Using the Skeleton of the Blob for Medical Rehabilitation Applications

2012

This article presents an image processing application for hand detection and tracking using the 4-connected skeleton of the segmentation mask. The system has been designed to be used with techniques of virtual reality to develop an interactive application for phantom limb pain reduction in therapeutic treatments. One of the major contributions is the design of a fast and accurate skeleton extractor, that has proven to be faster than those available in the literature. The skeleton allows the system to precisely detect the position of all the interest points of the hand (namely the fingers and the hand center). The system, composed of both the hand detector and tracker, and the virtual realit…

Computer sciencebusiness.industryDetectorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingVirtual realitySkeleton (category theory)Tracking (particle physics)Reduction (complexity)Virtual imageComputer graphics (images)SegmentationComputer visionArtificial intelligencebusiness
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Ridge-line optimal detector

2000

Image processing techniques have seen many developments in recent years. Starting from the pioneering work of Canny, Deriche developed a second order recursive filter capable of detecting stepped contours. However, there are other contour shapes that those filters struggle to detect. We describe a new optimal filter sensu Canny for detecting ridge-line contours. This is a third order recursive and even filter. It is dependent on three parameters by which detection accuracy is adjusted. The results obtained by applying this filter to (possibly noise- affected) images are compared with those in the work by Ziou. © 2000 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(00)00706-6)

Computer sciencebusiness.industryDetectorGeneral EngineeringImage processingAtomic and Molecular Physics and OpticsDeriche edge detectorNoiseFilter designSignal-to-noise ratioFilter (video)Computer visionRecursive filterArtificial intelligenceOptical filterbusinessDigital filterSmoothingOptical Engineering
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Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection

2012

Early detection of ventricular fibrillation (VF) is crucial for the success of the defibrillation therapy in automatic devices. A high number of detectors have been proposed based on temporal, spectral, and time-frequency parameters extracted from the surface electrocardiogram (ECG), showing always a limited performance. The combination ECG parameters on different domain (time, frequency, and time-frequency) using machine learning algorithms has been used to improve detection efficiency. However, the potential utilization of a wide number of parameters benefiting machine learning schemes has raised the need of efficient feature selection (FS) procedures. In this study, we propose a novel FS…

Computer sciencebusiness.industryDetectorGeneral EngineeringNonparametric statisticsFeature selectionPattern recognitionComputer Science ApplicationsDomain (software engineering)Support vector machineComputingMethodologies_PATTERNRECOGNITIONArtificial IntelligenceFeature (computer vision)Benchmark (computing)Artificial intelligencebusinessStatisticExpert Systems with Applications
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