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Semantic video fingerprinting and retrieval using face information / Costas Cotsaces in Signal processing. Image communication, Vol. 24 N° 7 (Août 2009) 

Public ISBD [article]  in Signal processing. Image communication > Vol. 24 N° 7 (Août 2009) . - pp. 598-613 Titre : Semantic video fingerprinting and retrieval using face information Type de document : texte imprimé Auteurs : Costas Cotsaces, Auteur ; Nikos Nikolaidis, Auteur ; Ioannis Pitas, Auteur Article en page(s) : pp. 598-613 Note générale : Electronique Langues : Anglais (eng) Mots-clés : Video  fingerprinting  Video  retrieval  Face  recognition  Semantic  features Index. décimale : 621.382 Dispositifs électroniques utilisant les effets des corps solides. Dispositifs semi-conducteurs Résumé : The management of large video databases, especially those containing motion picture and television data, is a major contemporary challenge. A very significant tool for this management is the ability to retrieve those segments that are perceptually similar to a query segment. Another similar but equally important task is determining if a query segment is a (possibly modified) copy of part of a video in the database. The basic way to perform these two tasks is to characterize each video segment with a unique representation called a signature. Using semantic information for the construction of the signatures is a good way to ensure robustness in retrieval and fingerprinting. Here a ubiquitous semantic feature, namely the existence and identity of human faces, will be used to construct the signature. A fast algorithm has been developed to quickly and robustly perform these two tasks on very large video databases. The prerequisite face recognition was performed by a commercial system. Having verified the basic efficacy of our algorithm on a database of real video from motion pictures and television series, we then proceed to further explore its performance in an artificial digital video database, which was created using a probabilistic model of the video creation process. This enabled us to explore variations in performance based on parameters that were impossible to control in a real video database. Furthermore, the suitability of the proposed approach for very large databases was tested using (artificial) data corresponding to hundreds or thousands of hours of video. DEWEY : 361.382 ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%235640%23 [...] [article] Semantic video fingerprinting and retrieval using face information [texte imprimé] / Costas Cotsaces, Auteur ; Nikos Nikolaidis, Auteur ; Ioannis Pitas, Auteur . - pp. 598-613. Electronique Langues : Anglais (eng) in Signal processing. Image communication > Vol. 24 N° 7 (Août 2009) . - pp. 598-613 Mots-clés : Video  fingerprinting  Video  retrieval  Face  recognition  Semantic  features Index. décimale : 621.382 Dispositifs électroniques utilisant les effets des corps solides. Dispositifs semi-conducteurs Résumé : The management of large video databases, especially those containing motion picture and television data, is a major contemporary challenge. A very significant tool for this management is the ability to retrieve those segments that are perceptually similar to a query segment. Another similar but equally important task is determining if a query segment is a (possibly modified) copy of part of a video in the database. The basic way to perform these two tasks is to characterize each video segment with a unique representation called a signature. Using semantic information for the construction of the signatures is a good way to ensure robustness in retrieval and fingerprinting. Here a ubiquitous semantic feature, namely the existence and identity of human faces, will be used to construct the signature. A fast algorithm has been developed to quickly and robustly perform these two tasks on very large video databases. The prerequisite face recognition was performed by a commercial system. Having verified the basic efficacy of our algorithm on a database of real video from motion pictures and television series, we then proceed to further explore its performance in an artificial digital video database, which was created using a probabilistic model of the video creation process. This enabled us to explore variations in performance based on parameters that were impossible to control in a real video database. Furthermore, the suitability of the proposed approach for very large databases was tested using (artificial) data corresponding to hundreds or thousands of hours of video. DEWEY : 361.382 ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%235640%23 [...]