Documents disponibles écrits par cet auteur

Perceptual-based quality assessment for audio–visual services / Junyong You in Signal processing. Image communication, Vol. 25 N° 7 (Août 2010) 

Public ISBD [article]  in Signal processing. Image communication > Vol. 25 N° 7 (Août 2010) . - pp. 482–501 Titre : Perceptual-based quality assessment for audio–visual services : A survey Type de document : texte imprimé Auteurs : Junyong You, Auteur ; Ulrich Reiter, Auteur ; Miska M. Hannuksela, Auteur Année de publication : 2012 Article en page(s) : pp. 482–501 Note générale : Electronique Langues : Anglais (eng) Mots-clés : Objective  quality  metric  Subjective  quality  assessment  HVS  Psychophysical  approach  Engineering  approach  Perception  Alignment  PEAQ  Semantic  importance Résumé : Accurate measurement of the perceived quality of audio–visual services at the end-user is becoming a crucial issue in digital applications due to the growing demand for compression and transmission of audio–visual services over communication networks. Content providers strive to offer the best quality of experience for customers linked to their different quality of service (QoS) solutions. Therefore, developing accurate, perceptual-based quality metrics is a key requirement in multimedia services. In this paper, we survey state-of-the-art signal-driven perceptual audio and video quality assessment methods independently, and investigate relevant issues in developing joint audio–visual quality metrics. Experiments with respect to subjective quality results have been conducted for analyzing and comparing the performance of the quality metrics. We consider emerging trends in audio–visual quality assessment, and propose feasible solutions for future work in perceptual-based audio–visual quality metrics. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596510000299 [article] Perceptual-based quality assessment for audio–visual services : A survey [texte imprimé] / Junyong You, Auteur ; Ulrich Reiter, Auteur ; Miska M. Hannuksela, Auteur . - 2012 . - pp. 482–501. Electronique Langues : Anglais (eng) in Signal processing. Image communication > Vol. 25 N° 7 (Août 2010) . - pp. 482–501 Mots-clés : Objective  quality  metric  Subjective  quality  assessment  HVS  Psychophysical  approach  Engineering  approach  Perception  Alignment  PEAQ  Semantic  importance Résumé : Accurate measurement of the perceived quality of audio–visual services at the end-user is becoming a crucial issue in digital applications due to the growing demand for compression and transmission of audio–visual services over communication networks. Content providers strive to offer the best quality of experience for customers linked to their different quality of service (QoS) solutions. Therefore, developing accurate, perceptual-based quality metrics is a key requirement in multimedia services. In this paper, we survey state-of-the-art signal-driven perceptual audio and video quality assessment methods independently, and investigate relevant issues in developing joint audio–visual quality metrics. Experiments with respect to subjective quality results have been conducted for analyzing and comparing the performance of the quality metrics. We consider emerging trends in audio–visual quality assessment, and propose feasible solutions for future work in perceptual-based audio–visual quality metrics. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596510000299

A semantic framework for video genre classification and event analysis / Junyong You in Signal processing. Image communication, Vol. 25 N° 4 (Avril 2010) 

Public ISBD [article]  in Signal processing. Image communication > Vol. 25 N° 4 (Avril 2010) . - pp. 287–302 Titre : A semantic framework for video genre classification and event analysis Type de document : texte imprimé Auteurs : Junyong You, Auteur ; Guizhong Liu, Auteur ; Andrew Perkis, Auteur Année de publication : 2012 Article en page(s) : pp. 287–302 Note générale : Electronique Langues : Anglais (eng) Mots-clés : Semantic  video  analysis  Probabilistic  model  Video  genre  classification  Event  analysis Résumé : Semantic video analysis is a key issue in digital video applications, including video retrieval, annotation, and management. Most existing work on semantic video analysis is mainly focused on event detection for specific video genres, while the genre classification is treated as another independent issue. In this paper, we present a semantic framework for weakly supervised video genre classification and event analysis jointly by using probabilistic models for MPEG video streams. Several computable semantic features that can accurately reflect the event attributes are derived. Based on an intensive analysis on the connection between video genres and the contextual relationship among events, as well as the statistical characteristics of dominant event, a hidden Markov model (HMM) and naive Bayesian classifier (NBC) based analysis algorithm is proposed for video genre classification. Another Gaussian mixture model (GMM) is built to detect the contained events using the same semantic features, whilst an event adjustment strategy is proposed according to an analysis on the GMM structure and pre-definition of video events. Subsequently, a special event is recognized based on the detected events by another HMM. The simulative experiments on video genre classification and event analysis using a large number of video data sets demonstrate the promising performance of the proposed framework for semantic video analysis. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596510000172 [article] A semantic framework for video genre classification and event analysis [texte imprimé] / Junyong You, Auteur ; Guizhong Liu, Auteur ; Andrew Perkis, Auteur . - 2012 . - pp. 287–302. Electronique Langues : Anglais (eng) in Signal processing. Image communication > Vol. 25 N° 4 (Avril 2010) . - pp. 287–302 Mots-clés : Semantic  video  analysis  Probabilistic  model  Video  genre  classification  Event  analysis Résumé : Semantic video analysis is a key issue in digital video applications, including video retrieval, annotation, and management. Most existing work on semantic video analysis is mainly focused on event detection for specific video genres, while the genre classification is treated as another independent issue. In this paper, we present a semantic framework for weakly supervised video genre classification and event analysis jointly by using probabilistic models for MPEG video streams. Several computable semantic features that can accurately reflect the event attributes are derived. Based on an intensive analysis on the connection between video genres and the contextual relationship among events, as well as the statistical characteristics of dominant event, a hidden Markov model (HMM) and naive Bayesian classifier (NBC) based analysis algorithm is proposed for video genre classification. Another Gaussian mixture model (GMM) is built to detect the contained events using the same semantic features, whilst an event adjustment strategy is proposed according to an analysis on the GMM structure and pre-definition of video events. Subsequently, a special event is recognized based on the detected events by another HMM. The simulative experiments on video genre classification and event analysis using a large number of video data sets demonstrate the promising performance of the proposed framework for semantic video analysis. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596510000172