Search results for "Automatic image annotation"

showing 10 items of 18 documents

Mathematical Methods in Image Processing and Computer Vision

2016

Image processing and computer vision are growing research fields that take advantage of the increasing power or modern computers linked with sophisticated techniques coming from many fields of expertise and in particular from mathematics. We present an introduction to some problems in computer vision and image processing and to some mathematical techniques and concepts that are nowadays routinely used to approach them.

Automatic image annotationbusiness.industryHuman visual system model3D reconstructionDigital image processingComputer vision and image processingComputer visionImage processingArtificial intelligenceImage analysisImage-based modeling and renderingbusiness
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Perceptual Image Representations for Support Vector Machine Image Coding

2007

Support-vector-machine image coding relies on the ability of SVMs for function approximation. The size and the profile of the e-insensitivity zone of the support vector regressor (SVR) at some specific image representation determines (a) the amount of selected support vectors (the compression ratio), and (b) the nature of the introduced error (the compression distortion). However, the selection of an appropriate image representation is a key issue for a meaningful design of the e-insensitivity profile. For example, in image-coding applications, taking human perception into account is of paramount relevance to obtain a good rate-distortion performance. However, depending on the accuracy of t…

Computer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionImage processingPermissionImage (mathematics)Support vector machineAutomatic image annotationDigital image processingComputer visionArtificial intelligenceImage warpingbusinessFeature detection (computer vision)
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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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Automatic Image Annotation Using Random Projection in a Conceptual Space Induced from Data

2018

The main drawback of a detailed representation of visual content, whatever is its origin, is that significant features are very high dimensional. To keep the problem tractable while preserving the semantic content, a dimen- sionality reduction of the data is needed. We propose the Random Projection techniques to reduce the dimensionality. Even though this technique is sub-optimal with respect to Singular Value Decomposition its much lower computational cost make it more suitable for this problem and in par- ticular when computational resources are limited such as in mobile terminals. In this paper we present the use of a "conceptual" space, automatically induced from data, to perform automa…

Computer sciencebusiness.industryDimensionality reductionRandom projectionFeature extractionRANDOM MAPPINGPattern recognition02 engineering and technology010501 environmental sciencesConceptual-space01 natural sciencesVisualizationAutomatic image annotationRandom-projectionHistogramSingular value decomposition0202 electrical engineering electronic engineering information engineeringImage-semantic020201 artificial intelligence & image processingArtificial intelligenceIMAGE ANNOTATIONbusinessCONCEPTUAL SPACE0105 earth and related environmental sciencesCurse of dimensionality
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Three-domain image representation for personal photo album management

2010

In this paper we present a novel approach for personal photo album management. Pictures are analyzed and described in three representation spaces, namely, faces, background and time of capture. Faces are automatically detected and rectified using a probabilistic feature extraction technique. Face representation is then produced by computing PCA (Principal Component Analysis). Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter bank. Temporal data is obtained through the extraction of EXIF (Exchangeable image file format) data. Each image in the collection is then automatically organized using a mean-shift clustering technique. While many system…

Computer sciencebusiness.industryFeature extractionCBIR - Content Based Image Retrieval automatic image annotation personal photo album managementComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingcomputer.file_formatGabor filterAutomatic image annotationHistogramFace (geometry)RGB color modelComputer visionArtificial intelligenceImage file formatsImage sensorCluster analysisbusinesscomputer
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Image Recognition through Incremental Discriminative Common Vectors

2010

An incremental approach to the discriminative common vector (DCV) method for image recognition is presented. Two different but equivalent ways of computing both common vectors and corresponding subspace projections have been considered in the particular context in which new training data becomes available and learned subspaces may need continuous updating. The two algorithms are based on either scatter matrix eigendecomposition or difference subspace orthonormalization as with the original DCV method. The proposed incremental methods keep the same good properties than the original one but with a dramatic decrease in computational burden when used in this kind of dynamic scenario. Extensive …

Computer sciencebusiness.industryPattern recognitionContext (language use)Machine learningcomputer.software_genreAutomatic image annotationDiscriminative modelImage textureScatter matrixU-matrixComputer visionArtificial intelligencebusinesscomputerSubspace topologyFeature detection (computer vision)
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Suitability of a content-based retrieval method in astronomical image databases

1996

Abstract Indexing and retrieval methods based on the image content are required to effectively use information from large repositories of digital images. Usually, the way to search for data and images in astronomical archives is via textual queries expressed in terms of constraints on observation parameters. In this paper we present a method for automatic extraction of images by using shape descriptions based on local symmetry. The proposed indexing methodology has been developed and tested inside JACOB, a prototypal system for content-based video database querying.

Digital imageInformation retrievalAutomatic image annotationComputer scienceContent (measure theory)Search engine indexingAstronomy and AstrophysicsVisual WordImage retrievalImage (mathematics)Content based retrievalVistas in Astronomy
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Brima: Low-Overhead Browser-Only Image Annotation Tool (Preprint)

2021

Image annotation and large annotated datasets are crucial parts within the Computer Vision and Artificial Intelligence this http URL the same time, it is well-known and acknowledged by the research community that the image annotation process is challenging, time-consuming and hard to scale. Therefore, the researchers and practitioners are always seeking ways to perform the annotations easier, faster, and at higher quality. Even though several widely used tools exist and the tools' landscape evolved considerably, most of the tools still require intricate technical setups and high levels of technical savviness from its operators and crowdsource contributors. In order to address such challenge…

FOS: Computer and information sciencesComputer Science - Machine LearningLow overheadProcess (engineering)Computer scienceComputer Vision and Pattern Recognition (cs.CV)Scale (chemistry)media_common.quotation_subjectComputer Science - Computer Vision and Pattern RecognitionMachine Learning (cs.LG)World Wide WebCrowdsourceAutomatic image annotationResearch communityQuality (business)Preprintmedia_common2021 IEEE International Conference on Image Processing (ICIP)
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Automatic Generation of Subject-Based Image Transitions

2011

This paper presents a novel approach for the automatic generation of image slideshows. Counter to standard cross-fading, the idea is to operate the image transitions keeping the subject focused in the intermediate frames by automatically identifying him/her and preserving face and facial features alignment. This is done by using a novel Active Shape Model and time-series Image Registration. The final result is an aesthetically appealing slideshow which emphasizes the subject. The results have been evaluated with a users’ response survey. The outcomes show that the proposed slideshow concept is widely preferred by final users w.r.t. standard image transitions.

Face processing; image morphing; image registrationComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationSubject (documents)Image processingimage morphingImage (mathematics)image registrationAutomatic image annotationActive shape modelFace (geometry)Face processingComputer visionArtificial intelligencebusinessFeature detection (computer vision)
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A Combined Fuzzy and Probabilistic Data Descriptor for Distributed CBIR

2009

With the wide diffusion of digital image acquisition devices, the cost of managing hundreds of digital images is quickly increasing. Currently, the main way to search digital image libraries is by keywords given by the user. However, users usually add ambiguos keywords for large set of images. A content-based system intended to automatically find a query image, or similar images, within the whole collection is needed. In our work we address the scenario where medical image collections, which nowadays are rapidly expanding in quantity and heterogeneity, are shared in a distributed system to support diagnostic and preventive medicine. Our goal is to produce an efficient content-based descript…

Fuzzy clustering distributed CBIR medical imagesFuzzy clusteringInformation retrievalComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProbabilistic logicDigital imagingcomputer.software_genreDigital imageAutomatic image annotationDigital image processingData miningImage analysisImage retrievalcomputer
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