Search results for "methodologie"

showing 10 items of 2141 documents

Splitting criterion for hierarchical motion estimation based on perceptual coding

1998

A new entropy-constrained motion estimation scheme using variable-size block matching is proposed. It is known that fixed-size block matching as used in most video codec standards is improved by using a multiresolution or multigrid approach. In this work, it is shown that further improvement is possible in terms of both the final bit rate achieved and the robustness of the predicted motion field if perceptual coding is taken into account in the motion estimation phase. The proposed scheme is compared against other variable- and fixed-size block matching algorithms.

business.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionQuarter-pixel motionMultigrid methodMotion fieldRobustness (computer science)Motion estimationComputer Science::MultimediaBit ratePerceptual codingCodecArtificial intelligenceElectrical and Electronic EngineeringbusinessMathematics
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Diversity in search strategies for ensemble feature selection

2005

Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. Ensembles allow us to achieve higher accuracy, which is often not achievable with single models. It was shown theoretically and experimentally that in order for an ensemble to be effective, it should consist of base classifiers that have diversity in their predictions. One technique, which proved to be effective for constructing an ensemble of diverse base classifiers, is the use of different feature subsets, or so-called ensemble feature selection. Many ensemble feature selection strategies incorporate diversity as an objective in the search for the best collection of feature subse…

business.industryContext (language use)Feature selectionMachine learningcomputer.software_genreEnsemble learningMeasure (mathematics)Random subspace methodEnsembles of classifiersComputingMethodologies_PATTERNRECOGNITIONHardware and ArchitectureFeature (computer vision)Signal ProcessingArtificial intelligenceData miningbusinesscomputerSoftwareSelection (genetic algorithm)Information SystemsMathematics
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Robustness of texture parameters for color texture analysis

2006

This article proposes to deal with noisy and variable size color textures. It also proposes to deal with quantization methods and to see how such methods change final results. The method we use to analyze the robustness of the textures consists of an auto-classification of modified textures. Texture parameters are computed for a set of original texture samples and stored into a database. Such a database is created for each quantization method. Textures from the set of original samples are then modified, eventually quantized and classified according to classes determined from a precomputed database. A classification is considered incorrect if the original texture is not retrieved. This metho…

business.industryCovariance matrixAutocorrelationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionMaxima and minimaQuantization (physics)Matrix (mathematics)Computer Science::GraphicsAutocorrelation matrixComputer Science::Computer Vision and Pattern RecognitionPrincipal component analysisRGB color modelComputer visionArtificial intelligencebusinessComputingMethodologies_COMPUTERGRAPHICSMathematicsSPIE Proceedings
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Plenoptic image watermarking to preserve copyright

2017

Common camera loses a huge amount of information obtainable from scene as it does not record the value of individual rays passing a point and it merely keeps the summation of intensities of all the rays passing a point. Plenoptic images can be exploited to provide a 3D representation of the scene and watermarking such images can be helpful to protect the ownership of these images. In this paper we propose a method for watermarking the plenoptic images to achieve this aim. The performance of the proposed method is validated by experimental results and a compromise is held between imperceptibility and robustness.

business.industryData_MISCELLANEOUSComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020207 software engineering02 engineering and technologyÒpticaImage (mathematics)GeographyRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPoint (geometry)Computer visionArtificial intelligencebusinessRepresentation (mathematics)Digital watermarkingThree-Dimensional Imaging, Visualization, and Display 2017
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Remote Sensing Geometric Corrections

2016

This article reviews the different aspects of geometrical processing of remote sensing data, discussing error sources and methods to determine the transformation from the image acquisition geometry to the output cartographic product. Resampling methods are discussed to transform the input image to the output geometry. Several practical examples of remote sensing platforms are discussed, including satellite cases and airborne sensors. Validation of the resulting geometrical processed products is also discussed. Spatial mosaicking techniques and multitemporal composites used to produce multisource integrated products and advanced applications are finally considered, keeping a perspective on t…

business.industryDistortion (optics)Perspective (graphical)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationGeographyTransformation (function)Remote sensing (archaeology)Image scalingGlobal Positioning SystemPreprocessorComputer visionArtificial intelligencebusinessRemote sensing
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Semisupervised kernel orthonormalized partial least squares

2012

This paper presents a semisupervised kernel orthonormalized partial least squares (SS-KOPLS) algorithm for non-linear feature extraction. The proposed method finds projections that minimize the least squares regression error in Hilbert spaces and incorporates the wealth of unlabeled information to deal with small size labeled datasets. The method relies on combining a standard RBF kernel using labeled information, and a generative kernel learned by clustering all available data. The positive definiteness of the kernels is proven, and the structure and information content of the derived kernels is studied. The effectiveness of the proposed method is successfully illustrated in standard UCI d…

business.industryFeature extractionNonlinear dimensionality reductionPattern recognitionComputingMethodologies_PATTERNRECOGNITIONKernel methodVariable kernel density estimationKernel (statistics)Radial basis function kernelPartial least squares regressionArtificial intelligenceCluster analysisbusinessMathematics2012 IEEE International Workshop on Machine Learning for Signal Processing
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Semisupervised Kernel Feature Extraction for Remote Sensing Image Analysis

2014

This paper presents a novel semisupervised kernel partial least squares (KPLS) algorithm for nonlinear feature extraction to tackle both land-cover classification and biophysical parameter retrieval problems. The proposed method finds projections of the original input data that align with the target variable (labels) and incorporates the wealth of unlabeled information to deal with low-sized or underrepresented data sets. The method relies on combining two kernel functions: the standard radial-basis-function kernel based on labeled information and a generative, i.e., probabilistic, kernel directly learned by clustering the data many times and at different scales across the data manifold. Th…

business.industryFeature extractionPattern recognitioncomputer.software_genreKernel principal component analysisComputingMethodologies_PATTERNRECOGNITIONKernel embedding of distributionsPolynomial kernelVariable kernel density estimationKernel (statistics)Radial basis function kernelGeneral Earth and Planetary SciencesPrincipal component regressionData miningArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerMathematicsRemote sensingIEEE Transactions on Geoscience and Remote Sensing
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Noise Robustness Analysis of Point Cloud Descriptors

2013

In this paper, we investigate the effect of noise on 3D point cloud descriptors. Various types of point cloud descriptors have been introduced in the recent years due to advances in computing power, which makes processing point cloud data more feasible. Most of these descriptors describe the orientation difference between pairs of 3D points in the object and represent these differences in a histogram. Earlier studies dealt with the performances of different point cloud descriptors; however, no study has ever discussed the effect of noise on the descriptors performances. This paper presents a comparison of performance for nine different local and global descriptors amidst 10 varying levels o…

business.industryGaussianComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPoint cloudPattern recognitionImpulse (physics)Impulse noisesymbols.namesakeComputingMethodologies_PATTERNRECOGNITIONGaussian noiseRobustness (computer science)Computer Science::Computer Vision and Pattern RecognitionHistogramComputer Science::MultimediasymbolsArtificial intelligencebusinessNormalMathematics
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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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