Search results for "ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION"

showing 10 items of 982 documents

Terrain data compression using wavelet-tiled pyramids for online 3D terrain visualization

2013

Last years have witnessed the widespread use of online terrain visualization applications. However, the significant improvements achieved in sensing technologies have allowed an increasing size of the terrain databases. These increasing sizes represent a serious drawback when terrain data must be transmitted and rendered at interactive rates. In this paper, we propose a novel wavelet-tiled pyramid for compressing terrain data that replaces the traditional multiresolution pyramid usually used in wavelet compression schemes. The new wavelet-tiled pyramid modifies the wavelet analysis and synthesis processes, allowing an efficient transmission and reconstruction of terrain data in those applic…

business.industryGeography Planning and DevelopmentComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformTerrainData_CODINGANDINFORMATIONTHEORYcomputer.file_formatTerrain renderingLibrary and Information SciencesVisualizationWaveletGeographyComputer graphics (images)JPEG 2000Computer visionArtificial intelligencePyramid (image processing)businesscomputerComputingMethodologies_COMPUTERGRAPHICSInformation SystemsData compressionInternational Journal of Geographical Information Science
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Latent Semantic Description of Iconic Scenes

2005

It is proposed an approach for the automatic description of scenes using a LSA–like technique. The described scenes are composed by a set of elements that can be geometric forms or iconic representation of objects. Every icon is characterized by a set of attributes like shape, colour and position. Each scene is related to a set of sentences describing their content. The proposed approach builds a data driven vector semantic space where the scenes and the sentences are mapped. A new scene can be mapped in this created space accordingly to a suitable metric. Preliminary experimental results show the effectiveness of the procedure.

business.industryLatent semantic analysisComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScene statisticsSpace (commercial competition)SemanticsSet (abstract data type)Metric (mathematics)Computer visionArtificial intelligenceRepresentation (mathematics)businessSentenceComputingMethodologies_COMPUTERGRAPHICS
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Spatio-Temporal Saliency Detection in Dynamic Scenes using Local Binary Patterns

2014

International audience; Visual saliency detection is an important step in many computer vision applications, since it reduces further processing steps to regions of interest. Saliency detection in still images is a well-studied topic. However, videos scenes contain more information than static images, and this additional temporal information is an important aspect of human perception. Therefore, it is necessary to include motion information in order to obtain spatio-temporal saliency map for a dynamic scene. In this paper, we introduce a new spatio-temporal saliency detection method for dynamic scenes based on dynamic textures computed with local binary patterns. In particular, we extract l…

business.industryLocal binary patternsComputer sciencemedia_common.quotation_subjectComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognition[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]video saliencyMotion (physics)visual saliencyKadir–Brady saliency detector[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Salience (neuroscience)PerceptionLBPSaliency mapComputer visionArtificial intelligencebusinessmedia_commonVisual saliency
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Perceptually weighted optical flow for motion-based segmentation in MPEG-4 paradigm

2000

In the MPEG-4 paradigm, the sequence must be described in terms of meaningful objects. This meaningful, high-level representation should emerge from low-level primitives such as optical flow and prediction error which are the basic elements of previous-generation video coders. The accuracy of the high-level models strongly depends on the robustness of the primitives used. It is shown how perceptual weighting in optical flow computation gives rise to better motion estimates which consistently improve motion-based segmentation compared to equivalent unweighted motion estimates.

business.industryMean squared prediction errorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowcomputer.file_formatPerceptual weightingOptical flow computationRobustness (computer science)Motion estimationComputer Science::MultimediaMPEG-4Computer visionSegmentationArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerMathematicsElectronics Letters
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Optical flow estimation from multichannel spherical image decomposition

2011

The problem of optical flow estimation is largely discussed in computer vision domain for perspective images. It was also proven that, in terms of optical flow analysis from these images, we have difficulty distinguishing between some motion fields obtained with little camera motion. The omnidirectional cameras provided images with large filed of view. These images contain global information about motion and allow to remove the ambiguity present in perspective case. Nevertheless, these images contain significant radial distortions that is necessary to take into account when treating these images to estimate the motion. In this paper, we shall describe new way to compute efficient optical fl…

business.industryPerspective (graphical)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowPhysics::OpticsMotion (geometry)Spherical imageImage (mathematics)WaveletComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingComputer visionComputer Vision and Pattern RecognitionArtificial intelligenceDecomposition method (constraint satisfaction)businessOmnidirectional antennaSoftwareMathematicsComputer Vision and Image Understanding
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Enhanced detection of contrast regions in echocardiograms by adaptive quantization

2002

The statistics of ultrasound echo images are governed by Rayleigh statistics. The authors derive some experimentally verifiable predictions of this theory, compare them with experimental results obtained from echocardiographic images, and derive a new color coding scheme, (adaptive quantization) that is adapted to the signal-dependent noise predicted by theory. This results in some technical advantages and in an improved discrimination of regions of the echo image that are enhanced by echo contrast material. >

business.industryQuantization (signal processing)Physics::Medical PhysicsEcho (computing)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONContrast (statistics)Noisesymbols.namesakeSignal-to-noise ratioColors of noisesymbolsProbability distributionComputer visionArtificial intelligenceRayleigh scatteringbusinessAlgorithmMathematics[1991] Proceedings Computers in Cardiology
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<title>Human cell texture analysis with quincunx spline wavelet transform</title>

1999

Wavelet transforms are efficient tools for texture analysis and classification. Separable techniques are classically used but present several drawbacks. First, diagonal coefficients contain poor information. Second, the other coefficients contain useful information only if the texture is oriented in the vertical and horizontal directions. So an approach of texture analysis by non-separable transform is proposed. An improved interscale resolution is allowed by the quincunx scheme and this analysis leads to only one detail image where no particular orientation is favored. New orthogonal isotropic filters for the decomposition are constructed by applying McClellan transform on one dimension B-…

business.industrySecond-generation wavelet transformStationary wavelet transformSpline waveletComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformSpline (mathematics)WaveletQuincunxComputer visionArtificial intelligencebusinessInfinite impulse responseAlgorithmMathematicsHuman Vision and Electronic Imaging IV
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Hidden Markov Random Field model and BFGS algorithm for Brain Image Segmentation

2016

Brain MR images segmentation has attracted a particular focus in medical imaging. The automatic image analysis and interpretation became a necessity. Segmentation is one of the key operations to provide a crucial decision support to physicians. Its goal is to simplify the representation of an image into items meaningful and easier to analyze. Hidden Markov Random Fields (HMRF) provide an elegant way to model the segmentation problem. This model leads to the minimization problem of a function. BFGS (Broyden-Fletcher-Goldfarb-Shanno algorithm) is one of the most powerful methods to solve unconstrained optimization problem. This paper presents how we combine HMRF and BFGS to achieve a good seg…

business.industrySegmentation-based object categorizationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionImage segmentationMachine learningcomputer.software_genreSørensen–Dice coefficientBroyden–Fletcher–Goldfarb–Shanno algorithmSegmentationArtificial intelligenceHidden Markov random fieldbusinessHidden Markov modelcomputerMathematicsProceedings of the Mediterranean Conference on Pattern Recognition and Artificial Intelligence
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<title>Multiresolution description of range images through 2D quincunx wavelet analysis</title>

1999

In this paper, we present a method for performing a multi- scale analysis on range images by using the wavelet transform, that is capable of revealing multi-resolution information. An accurate non-contact optical system based upon laser triangulation is used to determine the depth information of the object being scanned. The resulting range image is treated as a gray-level image by using a multi- resolution approach based on the generalization of the cascade algorithm using the quincunx wavelet transform. The quincunx wavelet assures very fine analysis. This method allows reconstruction of non-subsampled images that correspond to decompositions previously done at chosen scales. Multi-resolu…

business.industryStationary wavelet transformMultiresolution analysisComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformCascade algorithmIterative reconstructionWaveletQuincunxPolygon meshComputer visionArtificial intelligencebusinessMathematicsWavelet Applications VI
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A statistical model for magnitudes and angles of wavelet frame coefficients and its application to texture retrieval

2014

Abstract This paper presents a texture descriptor based on wavelet frame transforms. At each position in the image, and for each resolution level, we consider both vertical and horizontal wavelet detail coefficients as the components of a bivariate random vector. The magnitudes and angles of these vectors are computed. At each level the empirical histogram of magnitudes is modeled by a Generalized Gamma distribution, and the empirical histogram of angles is modeled by a different version of the von Mises distribution that accounts for histograms with 2 modes. Each texture is characterized by few parameters. A new distance is presented (based on the Kullback–Leibler divergence) that allows g…

business.industryTexture DescriptorGeneralized gamma distributionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionWaveletImage textureArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionHistogramSignal Processingvon Mises distributionComputer Vision and Pattern RecognitionArtificial intelligenceDivergence (statistics)businessImage retrievalSoftwareMathematicsPattern Recognition
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