Treffer: Semi-automatic photograph tagging by combining context with content-based information
Title:
Semi-automatic photograph tagging by combining context with content-based information
Authors:
Source:
Expert systems with applications. 42(1):203-211
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 1/2 p
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Inférence linéaire, régression, Linear inference, regression, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Systèmes informatiques et systèmes répartis. Interface utilisateur, Computer systems and distributed systems. User interface, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Analyse composante principale, Principal component analysis, Análisis componente principal, Analyse contenu, Content analysis, Análisis contenido, Analyse régression, Regression analysis, Análisis regresión, Annotation, Anotación, Apprentissage(intelligence artificielle), Learning (artificial intelligence), Evaluation performance, Performance evaluation, Evaluación prestación, Faciès, Facies, Filtre numérique, Digital filter, Filtro numérico, Filtre pondération, Weighting filter, Filtro ponderación, Fonction régression, Regression function, Función regresión, Gestion contenu, Content management, Gestión contenido, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Interpolation multivariable, Multivariate interpolation, Interpolación multivariable, Marquage, Tagging, Marcación, Multimédia, Multimedia, Métrique, Metric, Métrico, Reconnaissance forme, Pattern recognition, Reconocimiento patrón, Régression linéaire, Linear regression, Regresión lineal, Sensibilité contexte, Context aware, Sensibilidad contexto, Traitement image, Image processing, Procesamiento imagen, Vision ordinateur, Computer vision, Visión ordenador, Reconnaissance visage, Face recognition, Reconocimiento de cara, Context-aware multimedia, Geo-referenced photos, Metadata, People photo annotation, Personal photo collections
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
University of Campina Grande, Computer Science Department, Av. Aprigio Veloso, 882, Bodocongd, Campina Grande, Paraiba 58109-900, Brazil
Federal Institute of Education, Science and Technology of Paraiba ― Campus Monteiro, Monteiro, Paraíba, Brazil
Pontifical Catholic University of Rio de Janeiro, Av. Marques de São Vicente, 225 ― Rio de Janeiro, Rio de Janeiro 22451-900, Brazil
Federal University of Maranhão, Applied Computing Group NCA, Av. dos Portugueses, SN, São Luís, Maranhão 58109-900, Brazil
Federal Institute of Education, Science and Technology of Paraiba ― Campus Monteiro, Monteiro, Paraíba, Brazil
Pontifical Catholic University of Rio de Janeiro, Av. Marques de São Vicente, 225 ― Rio de Janeiro, Rio de Janeiro 22451-900, Brazil
Federal University of Maranhão, Applied Computing Group NCA, Av. dos Portugueses, SN, São Luís, Maranhão 58109-900, Brazil
ISSN:
0957-4174
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Mathematics
Telecommunications and information theory
Mathematics
Telecommunications and information theory
Accession Number:
edscal.28843394
Database:
PASCAL Archive
Weitere Informationen
This article proposes a semi-automatic technique for the annotation of people in photographs. The technique uses context and content information and is based on a weighted sum of estimators, which results in a list of the person's contacts that are more likely to be present in a photograph. Machine learning methods, such as multivariable linear regression and slope function, are adopted to filter and weight the estimators and eigenfaces for face recognition. The article also describes the results of experiments that were performed with a collection of 4050 photographs with 365 different people, which indicate that the proposed technique outperforms techniques that adopt only context or only content using as a performance metric the H-Hit rate of correct annotations.