Content-based discovery of multiple structures from episodes of recurrent TV programs based on grammatical inference

Abstract : TV program structuring is essential for program indexing and retrieval. Practically, various types of programs lead to a diversity of program structures. In addition, several episodes of a recurrent program might exhibit different structures. Previous work mostly relies on supervised approaches by adopting prior knowledge about program structures. In this paper, we address the problem of unsupervised program structuring with minimal prior knowledge about the programs. We propose an approach to identify multiple structures and infer structural grammars for recurrent TV programs of different types. It involves three sub-problems: i) we determine the structural elements contained in programs with minimal knowledge about which type of elements may be present; ii) we identify multiple structures for the programs if any and model the structures of programs; iii) we generate the structural grammar for each corresponding structure. Finally, we conduct use cases on real recurrent programs of three different types to demonstrate the effectiveness of proposed approach.
Type de document :
Communication dans un congrès
International Conference on Multimedia Modelling, Jan 2015, Sydney, Australia. 2015
Liste complète des métadonnées

Littérature citée [14 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-01089237
Contributeur : Guillaume Gravier <>
Soumis le : lundi 1 décembre 2014 - 14:06:24
Dernière modification le : jeudi 15 novembre 2018 - 11:58:51
Document(s) archivé(s) le : lundi 2 mars 2015 - 13:31:52

Fichier

MMM.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01089237, version 1

Citation

Bingqing Qu, Félicien Vallet, Jean Carrive, Guillaume Gravier. Content-based discovery of multiple structures from episodes of recurrent TV programs based on grammatical inference. International Conference on Multimedia Modelling, Jan 2015, Sydney, Australia. 2015. 〈hal-01089237〉

Partager

Métriques

Consultations de la notice

895

Téléchargements de fichiers

164