Search results for "Computer Vision and Pattern Recognition"

showing 10 items of 997 documents

Adapted processing of catadioptric images using polarization imaging

2009

A non parametric method that defines a pixel neighborhood within catadioptric images is presented in this paper. It is based on an accurate modeling of the mirror shape by using polarization imaging. Unlike the most of current processing methods in the literature, this method is non-parametric and can deal with the deformation of catadioptric images. This paper demonstrates how an appropriate neighborhood can be derived from the polarization parameters by estimation of the degree of polarization and the angle of polarization which in return directly provide an adapted neighborhood of each pixel that can be used to perform image derivation, edge detection, interest point detection and namely…

Pixelbusiness.industry010401 analytical chemistryNonparametric statistics[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technologyImage planePolarization (waves)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural sciencesEdge detection0104 chemical sciencesInterest point detectionCatadioptric system[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Computer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineeringDegree of polarization020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessComputingMilieux_MISCELLANEOUSMathematics
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<title>Spectral/spatial integration effects on information extraction from multispectral data: multiresolution approaches</title>

1995

New techniques for information extraction from multispectral data require physical modeling to understand the energy transfer at the atmosphere/surface interface and to develop appropriate inversion procedures, in combination with advanced processing techniques. A multi-step procedure is proposed in this work: the first step implies a binary decision about the second step to be applied in each case. If the pixel is considered as being a `pure' pixel, through a spectral/spatial classification procedure based on multiresolution techniques, then numerical inversion techniques, based on a multiple-scattering reflectance model, are used to extract parameters representing specific surface propert…

Pixelbusiness.industryBinary decision diagramComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionAtmospheric modelcomputer.software_genreData modelingInformation extractionGeographyComputer Science::Computer Vision and Pattern RecognitionSpatial ecologyComputer visionArtificial intelligenceSpectral resolutionbusinessImage resolutioncomputerSPIE Proceedings
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Image Colorization Method Using Texture Descriptors and ISLIC Segmentation

2017

We present a new colorization method to assign color to a grayscale image based on a reference color image using texture descriptors and Improved Simple Linear Iterative Clustering (ISLIC). Firstly, the pixels of images are classified using Support Vector Machine (SVM) according to texture descriptors, mean luminance, entropy, homogeneity, correlation, and local binary pattern (LBP) features. Then, the grayscale image and the color image are segmented into superpixels, which are obtained by ISLIC to produce more uniform and regularly shaped superpixels than those obtained by SLIC, and the classified images are further post-processed combined with superpixles for removing erroneous classific…

Pixelbusiness.industryColor imageLocal binary patternsComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionImage segmentationGrayscaleImage textureComputer Science::Computer Vision and Pattern RecognitionArtificial intelligencebusinessCluster analysisComputingMethodologies_COMPUTERGRAPHICS
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Texture Discrimination Using Hierarchical Complex Networks

2008

Texture analysis represents one of the main areas in image processing and computer vision. The current article describes how complex networks have been used in order to represent and characterized textures. More speci?cally, networks are derived from the texture images by expressing pixels as network nodes and similarities between pixels as network edges. Then, measurements such as the node degree, strengths and clustering coe?cient are used in order to quantify properties of the connectivity and topology of the analyzed networks. Because such properties are directly related to the structure of the respective texture images, they can be used as features for characterizing and classifying te…

Pixelbusiness.industryComputer scienceNode (networking)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONChaos gamePattern recognitionImage processingComplex networkTexture (geology)Computer Science::Computer Vision and Pattern RecognitionArtificial intelligenceCluster analysisbusinessTopology (chemistry)
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Meta-Tracking for Video Scene Understanding

2013

International audience; This paper presents a novel method to extract dominant motion patterns (MPs) and the main entry/exit areas from a surveillance video. The method first computes motion histograms for each pixel and then converts it into orientation distribution functions (ODFs). Given these ODFs, a novel particle meta-tracking procedure is launched which produces meta-tracks, i.e. particle trajectories. As opposed to conventional tracking which focuses on individual moving objects, meta-tracking uses particles to follow the dominant flow of the traffic. In a last step, a novel method is used to simultaneously identify the main entry/exit areas and recover the predominant MPs. The meta…

Pixelbusiness.industryComputer scienceOrientation (computer vision)Feature extractionChaotic[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineering02 engineering and technologyTracking (particle physics)[ 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]Video trackingHistogramMotion estimation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligencebusiness
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Affine camera calibration from homographies of parallel planes

2010

This paper deals with the problem of retrieving the affine structure of a scene from two or more images of parallel planes. We propose a new approach that is solely based on plane homographies, calculated from point correspondences, and that does not require the recovery of the 3D structure of the scene. Neither vanishing points nor lines need to be extracted from the images. The case of a moving camera with constant intrinsic parameters and the one of cameras with possibly different parameters are both addressed. Extensive experiments with both synthetic and real images have validated our approach.

Pixelbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONIterative reconstructionReal imagePlane (Unicode)Computer Science::Computer Vision and Pattern RecognitionPoint (geometry)Computer visionAffine transformationArtificial intelligenceVanishing pointbusinessCamera resectioningMathematics2010 IEEE International Conference on Image Processing
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Maximum likelihood for target location in the presence of substitutive noise .

2001

We consider the optimal likelihood algorithm for the estimation of a target location when the images are corrupted by substitutive noise. We show the relationship between the optimal algorithm and the sliced orthogonal nonlinear generalized (SONG) correlation. The SONG correlation is based on the application of a linear correlation to corresponding binary slices of both the input scene and the reference object with appropriate weight factors. For a particular case, we show that the optimal strategy is a function of only the number of pixels for which the gray values in the noisy image match the ones of the reference image when the substitutive noise is uniformly distributed. This is exactly…

Pixelbusiness.industryMaterials Science (miscellaneous)Binary numberImage processing02 engineering and technologyFunction (mathematics)021001 nanoscience & nanotechnology01 natural sciencesIndustrial and Manufacturing EngineeringImage (mathematics)010309 opticsNoiseOpticsComputer Science::Computer Vision and Pattern Recognition[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Computer Science::Multimedia0103 physical sciencesPattern recognition (psychology)Business and International Management0210 nano-technologybusinessAlgorithmLinear filterMathematics
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Architectural Scenes Reconstruction from Uncalibrated Photos and Map Based Model Knowledge

2001

In this paper we consider the problem of reconstructing architectural scenes from multiple photographs taken from arbitrarily viewpoints. The original contribution of this work is the use of a map as a source of a priori knowledge and geometric constraints in order to obtain in a fast and simple way a detailed model of a scene. We suppose images are uncalibrated and have at least one planar structure as a facade for exploiting the planar homography induced between world plane and image to calculate a first estimation of the projection matrix. Estimations are improved by using correspondences between images and map. We show how these simple constraints can be used to calibrate the cameras, t…

Plane (geometry)business.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONTriangulation (social science)Triangulation (computer vision)Iterative reconstructionProjection (linear algebra)Image (mathematics)Trifocal tensorSimple (abstract algebra)Computer Science::Computer Vision and Pattern RecognitionHomographyComputer visionArtificial intelligencebusiness
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The ATHENA X-ray Integral Field Unit (X-IFU)

2018

Event: SPIE Astronomical Telescopes + Instrumentation, 2018, Austin, Texas, United States.

Point spread functionPhotonAstrophysics::High Energy Astrophysical PhenomenaField 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 EngineeringCondensed Matter PhysicLarge format01 natural sciences7. Clean energySpace telescopeslaw.inventionTelescopePhysics::Popular PhysicsSettore FIS/05 - Astronomia E AstrofisicaOpticslawPhysics::Plasma Physics0103 physical sciencesElectronicAthenaOptical and Magnetic MaterialsSpectral resolutionElectrical and Electronic Engineering010306 general physics010303 astronomy & astrophysicsInstrumentationPhysicsSpectrometerbusiness.industryElectronic Optical and Magnetic MaterialApplied MathematicsDetectorAstrophysics::Instrumentation and Methods for AstrophysicsComputer Science Applications1707 Computer Vision and Pattern RecognitionCondensed Matter Physics115 Astronomy Space sciencePhysics::History of PhysicsApplied MathematicSpace telescopeX-ray Integral Field UnitX-ray spectroscopybusiness
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Left-handed metamaterial coatings for subwavelength-resolution imaging

2012

We report on a procedure to improve the resolution of far-field imaging by using a neighboring high-index medium that is coated with a left-handed metamaterial. The resulting plot can also exhibit an enhanced transmission by considering proper conditions to retract backscattering. Based on negative refraction, geometrical aberrations are considered in detail since they may cause a great impact in this sort of diffraction-unlimited imaging by reducing its resolution power. We employ a standard aberration analysis to refine the asymmetric configuration of metamaterial superlenses. We demonstrate that low-order centrosymmetric aberrations can be fully corrected for a given object plane. For su…

Point spread functionPhysicsbusiness.industryPlane (geometry)Resolution (electron density)MetamaterialPhysics::OpticsImage planeAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsOpticsTransmission (telecommunications)Negative refractionImage formation theoryMetamaterialsComputer Vision and Pattern RecognitionTransmission coefficientbusinessAberration compensationÓptica
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