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Multimedia classification of movie shots using low-level and semantic features

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text
 

Genre(s)

article
 

Forme(s)

document numérique
 

Cette ressource est disponible chez l'organisme suivant : Ircam - Centre Pompidou

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Titre

Multimedia classification of movie shots using low-level and semantic features
 

Nom(s)

Delezoide, Bertrand (auteur)
 

Publication

2005
 

Description

Sujet(s)

Multimodal information fusion   statistical modeling   video indexing   SVM   Bayesian network   early fusion   late fusion.
 

Résumé

Movie shots categorization may be approached by using audio and visual features for inferring high-level information about a movie shot. Low-level audio and visual features such as color and MFCC and mid-level features such as sky and speech detection have been used in multimedia understanding research. However, integrating all this features in a classifier remains a subject of study. In this paper, we propose a multimedia SVM fusion model, presented in Figure 1, for integrating knowledge from low-level and semantic features extracted from auditory and visual signal for scene classification of movie shots. We also compare our method with common approaches for feature integration based on Bayesian Network. Our computational results show that our model can achieve significantly better and more stable performance than other strategies.
 

Note(s)

Contribution au colloque ou congrès : ACM Multimédia
 

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Date de la notice

2010-02-25 01:00:00
 

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