Search results for " image retrieval"

showing 10 items of 29 documents

Real Time Robust Embedded Face Detection Using High Level Description

2011

Face detection is a fundamental prerequisite step in the process of face recognition. It consists of automatically finding all the faces in an image despite the considerable variations of lighting, background, appearance of people, position/orientation of faces, and their sizes. This type of object detection has the distinction of having a very large intra-class, making it a particularly difficult problem to solve, especially when one wishes to achieve real time processing. A human being has a great ability to analyze images. He can extract the information about it and focus only on areas of interest (the phenomenon of attention). Thereafter he can detect faces in an extremely reliable way.…

Boosting (machine learning)business.industryComputer scienceReal-time computingDetector02 engineering and technologyContent-based image retrievalFacial recognition systemObject detection020202 computer hardware & architecture[INFO.INFO-ES] Computer Science [cs]/Embedded Systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer vision[INFO.INFO-ES]Computer Science [cs]/Embedded SystemsArtificial intelligence[ INFO.INFO-ES ] Computer Science [cs]/Embedded SystemsbusinessLinear combinationFace detectionImplementation
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Semantic and topological classification of images in magnetically guided capsule endoscopy

2012

International audience; Magnetically-guided capsule endoscopy (MGCE) is a nascent technology with the goal to allow the steering of a capsule endoscope inside a water filled stomach through an external magnetic field. We developed a classification cascade for MGCE images with groups images in semantic and topological categories. Results can be used in a post-procedure review or as a starting point for algorithms classifying pathologies. The first semantic classification step discards over-/under-exposed images as well as images with a large amount of debris. The second topological classification step groups images with respect to their position in the upper gastrointestinal tract (mouth, es…

Color histogramComputer scienceFeature extraction[INFO.INFO-IM] Computer Science [cs]/Medical ImagingImage processingFundus (eye)Content-based image retrieval030218 nuclear medicine & medical imaginglaw.invention03 medical and health sciences0302 clinical medicineDiscriminative modelCapsule endoscopylaw[INFO.INFO-IM]Computer Science [cs]/Medical ImagingmedicineUpper gastrointestinalComputer visionSegmentationAntrumContextual image classification[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industryStomachmedicine.anatomical_structureFeature (computer vision)Duodenum030211 gastroenterology & hepatologyArtificial intelligencebusiness
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A naive relevance feedback model for content-based image retrieval using multiple similarity measures

2010

This paper presents a novel probabilistic framework to process multiple sample queries in content based image retrieval (CBIR). This framework is independent from the underlying distance or (dis)similarity measures which support the retrieval system, and only assumes mutual independence among their outcomes. The proposed framework gives rise to a relevance feedback mechanism in which positive and negative data are combined in order to optimally retrieve images according to the available information. A particular setting in which users interactively supply feedback and iteratively retrieve images is set both to model the system and to perform some objective performance measures. Several repo…

Computer scienceRelevance feedbackContent-based image retrievalcomputer.software_genreSimilitudeSet (abstract data type)Similarity (network science)Artificial IntelligenceSignal ProcessingComputer Vision and Pattern RecognitionData miningImage retrievalcomputerSoftwareIndependence (probability theory)Pattern Recognition
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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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An improved distance-based relevance feedback strategy for image retrieval

2013

Most CBIR (content based image retrieval) systems use relevance feedback as a mechanism to improve retrieval results. NN (nearest neighbor) approaches provide an efficient method to compute relevance scores, by using estimated densities of relevant and non-relevant samples in a particular feature space. In this paper, particularities of the CBIR problem are exploited to propose an improved relevance feedback algorithm based on the NN approach. The resulting method has been tested in a number of different situations and compared to the standard NN approach and other existing relevance feedback mechanisms. Experimental results evidence significant improvements in most cases.

Computer sciencebusiness.industryFeature vectorRelevance feedbackMachine learningcomputer.software_genreContent-based image retrievalk-nearest neighbors algorithmSignal ProcessingRelevance (information retrieval)Computer Vision and Pattern RecognitionArtificial intelligencebusinesscomputerImage retrievalDistance basedImage and Vision Computing
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Interactive Image Retrieval Using Smoothed Nearest Neighbor Estimates

2010

Relevance feedback has been adopted by most recent Content Based Image Retrieval systems to reduce the semantic gap that exists between the subjective similarity among images and the similarity measures computed in a given feature space. Distance-based relevance feedback using nearest neighbors has been recently presented as a good tradeoff between simplicity and performance. In this paper, we analyse some shortages of this technique and propose alternatives that help improving the efficiency of the method in terms of the retrieval precision achieved. The resulting method has been evaluated on several repositories which use different feature sets. The results have been compared to those obt…

Computer sciencebusiness.industryFeature vectorRelevance feedbackPattern recognitionContent-based image retrievalcomputer.software_genrek-nearest neighbors algorithmSimilarity (network science)Feature (computer vision)Visual WordArtificial intelligenceData miningbusinessImage retrievalcomputer
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Clustering techniques for personal photo album management

2009

In this work we propose a novel approach for the automatic representation of pictures achieving at more effective organization of personal photo albums. Images are analyzed and described in multiple representation spaces, namely, faces, background and time of capture. Faces are automatically detected, rectified and represented projecting the face itself in a common low-dimensional eigenspace. Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter bank. Faces, time and background information of each image in the collection is automatically organized using a mean-shift clustering technique. Given the particular domain of personal photo libraries, wh…

Gabor filterspattern clusteringComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONcontent-based retrievalFacial recognition systemimage retrievalimage colour analysisHistogramComputer visionimage representationElectrical and Electronic EngineeringCluster analysisImage retrievalMathematicsbusiness.industryCBIR - Content Based Image Retrieval automatic image annotation personal photo album managementPattern recognitionAtomic and Molecular Physics and OpticsComputer Science ApplicationsData setAutomatic image annotationFace (geometry)RGB color modelArtificial intelligenceeigenvalues and eigenfunctionsbusinessface recognitionJournal of Electronic Imaging
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AUTOMATIC ORGANIZATION OF MULTIMEDIA DATA COLLECTIONS

2014

La fotografia digitale ha avuto uno sviluppo sempre crescente negli ultimi dieci anni. Prima la diminuzione dei prezzi delle apparecchiature di acquisizione e poi l’integrazione di queste nei dispositivi portatili di uso quotidiano (i.e. smartphone, tablet) ha permesso a chiunque di potere creare e conservare semplicemente un enorme numero di immagini. Inoltre l’immagine stessa é diventata uno strumento di comunicazione, portando alla nascita di social networks basati unicamente sulla condivisione di fotografie (flickr, instagram, etc...). La gestione di tali quantitá di dati é quindi diventato un problema reale per molti utenti, in quanto il ritrovamento e l’organizzazione di questi dati é…

Image collections personal photo collection image retrieval collection fusion
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<title>Combining multiple image descriptions for browsing and retrieval</title>

2000

Retrieving images form large collections using image content is an important problem, in this multimedia age. A quick content-based visual access to the stored image is capital for efficient navigation through image collections. In this paper we introduce several techniques which characterize color homogeneous object and their spatial relationships for efficient content-based image retrieval. We present a region growing technique for efficient color homogeneous objects segmentation and extend the 2D string to an accurate description of spatial information and relationships. In order to improve content-based image retrieval, our method emphasized several objectives, such as: automated extrac…

Information retrievalComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONContent-based image retrievalAutomatic image annotationImage textureRegion growingHuman–computer information retrievalComputer visionSegmentationVisual WordArtificial intelligencebusinessImage retrievalFeature detection (computer vision)SPIE Proceedings
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Automatic building of a visual interface for content-based multiresolution retrieval of paleontology images

2001

In this article we present research work in the field of content-based image retrieval in large databases applied to the paleontology image database of the Universite´ de Bourgogne, Dijon, France, called ‘‘TRANS’TYFIPAL.’’ Our indexing method is based on multiresolution decomposition of database images using wavelets. For each family of paleontology images we try to find a model image that represents it. The K-means automatic classification algorithm divides the space of parameters into several clusters. A model image for each cluster is computed from the wavelet transform of each image of the cluster. Then a search tree is built to offer users a graphic interface for retrieving images. So …

Information retrievalContextual image classificationComputer sciencebusiness.industrySearch engine indexingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020206 networking & telecommunicationsImage processing02 engineering and technologyContent-based image retrievalAtomic and Molecular Physics and OpticsSearch treeComputer Science ApplicationsPaleontologyAutomatic image annotation[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionVisual WordArtificial intelligenceElectrical and Electronic EngineeringbusinessImage retrievalComputingMilieux_MISCELLANEOUS
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