Search results for "Computer Vision and Pattern Recognition"

showing 10 items of 997 documents

Gabor filtering for feature extraction on complex images: application to defect detection on semiconductors

2006

AbstractThis paper is an extension of previous work on the image segmentation of electronic structures on patterned wafers to improve the defect detection process on optical inspection tools. Die-to-die wafer inspection is based upon the comparison of the same area on two neighbourhood dies. The dissimilarities between the images are a result of defects in this area of one of the dies. The noise level can vary from one structure to the other, within the same image. Therefore, segmentation is needed to create a mask and apply an optimal threshold in each region. Contrast variation on the texture can affect the response of the parameters used for the segmentation. This paper shows a method of…

Computer scienceSegmentation-based object categorizationbusiness.industryFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionImage segmentationThresholdingMedia TechnologyWaferComputer visionSegmentationComputer Vision and Pattern RecognitionArtificial intelligencebusinessClassifier (UML)The Imaging Science Journal
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Uncalibrated Reconstruction: An Adaptation to Structured Light Vision

2003

Abstract Euclidean reconstruction from two uncalibrated stereoscopic views is achievable from the knowledge of geometrical constraints about the environment. Unfortunately, these constraints may be quite difficult to obtain. In this paper, we propose an approach based on structured lighting, which has the advantage of providing geometrical constraints independent of the scene geometry. Moreover, the use of structured light provides a unique solution to the tricky correspondence problem present in stereovision. The projection matrices are first computed by using a canonical representation, and a projective reconstruction is performed. Then, several constraints are generated from the image an…

Computer scienceStereoscopy02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural scienceslaw.invention010309 optics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Projection (mathematics)Artificial Intelligencelaw0103 physical sciencesEuclidean geometry0202 electrical engineering electronic engineering information engineeringComputer visionCorrespondence problemComputingMilieux_MISCELLANEOUSbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Mobile robot navigationSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionAffine transformationArtificial intelligencebusinessSoftwareStructured light
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The Athena X-ray Integral Field Unit (X-IFU)

2016

Event: SPIE Astronomical Telescopes + Instrumentation, 2016, Edinburgh, United Kingdom.

Computer science[ PHYS.ASTR ] Physics [physics]/Astrophysics [astro-ph]AstronomyObservatoriesField of viewAthena; Instrumentation; Space telescopes; X-ray Integral Field Unit; X-ray spectroscopy; Electronic Optical and Magnetic Materials; Condensed Matter Physics; Computer Science Applications1707 Computer Vision and Pattern Recognition; Applied Mathematics; Electrical and Electronic Engineering7. Clean energy01 natural scienceslaw.inventionSettore FIS/05 - Astronomia E AstrofisicalawObservatoryAthena Instrumentation Space telescopes X-ray spectroscopy X-ray Integral Field UnitAthena010303 astronomy & astrophysicsInstrumentation[ PHYS.PHYS.PHYS-INS-DET ] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]SpectroscopyHigh Energy Astrophysical Phenomena (astro-ph.HE)Equipment and servicesApplied MathematicsX-rayComputer Science Applications1707 Computer Vision and Pattern RecognitionCondensed Matter PhysicsProceedings of SPIE - the International Society for Optical EngineeringX-ray spectroscopyAstrophysics - Instrumentation and Methods for AstrophysicsAstrophysics - High Energy Astrophysical PhenomenaHigh energy astrophysicsAstrophysics - Cosmology and Nongalactic AstrophysicsCosmology and Nongalactic Astrophysics (astro-ph.CO)Spectral resolutionFOS: Physical sciencesMinute of arcSpace telescopesTelescope0103 physical sciencesX-raysElectronicOptical and Magnetic Materials[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]Spectral resolutionElectrical and Electronic Engineering010306 general physicsSpectroscopyInstrumentation and Methods for Astrophysics (astro-ph.IM)Remote sensingPixelAstrophysics - Astrophysics of GalaxiesAstrophysics of Galaxies (astro-ph.GA)X-ray Integral Field Unit[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]Telescopes
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Tracking Hands in Interaction with Objects: A Review

2017

Markerless vision-based 3D hand motion tracking is a key and popular component for interaction studies in many domains such as virtual reality and natural human-computer interfaces. While this research field has been well studied in the last decades, most approaches have considered the human hand in isolation and not in action or in interaction with the environment or the other articulated human body parts. Employing contextual information about the surrounding environment (e.g. the shape, the texture, and the posture of the object in the hand) can remarkably constrain the tracking problem. The goal of this survey is to develop an up-to-date taxonomy of existing vision-based hand tracking m…

Computer science[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineering02 engineering and technologyVirtual reality[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Object (philosophy)Field (computer science)Domain (software engineering)Action (philosophy)Human–computer interactionTaxonomy (general)Component (UML)[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPoseComputingMilieux_MISCELLANEOUS
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A combined analysis to extract objects in remote sensing images

1999

Abstract This paper describes an object recognition system to extract shape information from remote sensing images. One of the goals is to determine if towers and power lines can be seen on one-meter imagery and how much ground conditions can influence the resolution power of the recognition algorithms. To this end, an integrated analysis system has been implemented inside the Remote Sensing Imaging System (RSIS). The methodology consists in the combination of statistical and structural information. It has been tested on real images and it will be integrated in an automatic system for the assessment of post storm damage.

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCognitive neuroscience of visual object recognitionMathematical morphologyReal imagePower (physics)Artificial IntelligenceRemote sensing (archaeology)Signal ProcessingComputer visionComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareRemote sensingPattern Recognition Letters
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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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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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Reduction of the number of spectral bands in Landsat images: a comparison of linear and nonlinear methods

2006

We describe some applications of linear and nonlinear pro- jection methods in order to reduce the number of spectral bands in Land- sat multispectral images. The nonlinear method is curvilinear component analysis CCA, and we propose an adapted optimization of it for image processing, based on the use of principal-component analysis PCA, a linear method. The principle of CCA consists in reproducing the topol- ogy of the original space projection points in a reduced subspace, keep- ing the maximum of information. Our conclusions are: CCA is an im- provement for dimension reduction of multispectral images; CCA is really a nonlinear extension of PCA; CCA optimization through PCA called CCAinitP…

Computer sciencebusiness.industryDimensionality reductionQuantization (signal processing)Multispectral imageGeneral EngineeringImage processingPattern recognitionImage segmentationSpectral bandsNonlinear Sciences::Cellular Automata and Lattice GasesAtomic and Molecular Physics and OpticsStatistics::Machine LearningComputer Science::Computer Vision and Pattern RecognitionPrincipal component analysisComputer visionArtificial intelligenceProjection (set theory)businessSubspace topologyOptical Engineering
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Automatic place detection and localization in autonomous robotics

2007

This paper presents an approach for the simultaneous learning and recognition of places applied to autonomous robotics. While noteworthy results have been achieved with respect to off-line training process for appearance-based navigation, novel issues arise when recognition and learning are simultaneous and unsupervised processes. The approach adopted here uses a Gaussian mixture model estimated by a novel incremental MML-EM to model the probability distribution of features extracted by image-preprocessing. A place detector decides which features belong to which place integrating odometric information and a hidden Markov model. Tests demonstrate that the proposed system performs as well as …

Computer sciencebusiness.industryFeature extractionRoboticsComputer Science Applications1707 Computer Vision and Pattern RecognitionMixture modelMachine learningcomputer.software_genreObject detectionsymbols.namesakeControl and Systems EngineeringsymbolsRobotUnsupervised learningArtificial intelligenceHidden Markov modelbusinessGaussian processcomputerSoftware1707
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Multimodal 2D Image to 3D Model Registration via a Mutual Alignment of Sparse and Dense Visual Features

2018

International audience; Many fields of application could benefit from an accurate registration of measurements of different modalities over a known 3D model. However, aligning a 2D image to a 3D model is a challenging task and is even more complex when the two have a different modality. Most of the 2D/3D registration methods are based on either geometric or dense visual features. Both have their own advantages and their own drawbacks. We propose, in this paper, to mutually exploit the advantages of one feature type to reduce the drawbacks of the other one. For this, an hybrid registration framework has been designed to mutually align geometrical and dense visual features in order to obtain …

Computer sciencebusiness.industryFeature extraction[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineering3d model02 engineering and technologySolid modeling[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Visualization[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringRobot[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]020201 artificial intelligence & image processingComputer visionArtificial intelligencebusiness
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