Search results for "content-based retrieval"

showing 2 items of 2 documents

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
researchProduct

Adding Knowledge Extracted by Association Rules into Similarity Queries

2010

International audience; In this paper, we propose new techniques to improve the quality of similarity queries over image databases performing association rule mining over textual descriptions and automatically extracted features of the image content. Based on the knowledge mined, each query posed is rewritten in order to better meet the user expectations. We propose an extension of SQL aimed at exploring mining processes over complex data, generating association rules that extract semantic information from the textual description superimposed to the extracted features, thereafter using them to rewrite the queries. As a result, the system obtains results closer to the user expectation than i…

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Webuser expectation[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer scienceInformationSystems_DATABASEMANAGEMENTsimilarity queriescontent-based retrievalassociation rules[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][SCCO.COMP] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]SQL extensionquery rewriting[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
researchProduct