Automatic propagation of manual annotations for multimodal person identification in TV shows

Mateusz Budnik 1 Johann Poignant 1 Laurent Besacier 2 Georges Quénot 3
1 LIG - Laboratoire d'Informatique de Grenoble
2 GETALP - Groupe d’Étude en Traduction Automatique/Traitement Automatisé des Langues et de la Parole
LIG - Laboratoire d'Informatique de Grenoble
3 MRIM - Modélisation et Recherche d’Information Multimédia [Grenoble]
LIG - Laboratoire d'Informatique de Grenoble, Inria - Institut National de Recherche en Informatique et en Automatique
Abstract : In this paper an approach to human annotation propagation for person identification in the multimodal context is proposed. A system is used, which combines speaker diarization and face clustering to produce multimodal clusters. The whole multimodal clusters are later annotated rather than just single tracks, which is done by propagation. Optical character recogni- tion systems provides initial annotation. Four different strategies, which select candidates for annotation, are tested. The initial results of annotation propagation are promising. With the use of a proper active learning selection strategy the human annotator involvement could be reduced even further.
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Mateusz Budnik, Johann Poignant, Laurent Besacier, Georges Quénot. Automatic propagation of manual annotations for multimodal person identification in TV shows. 12th International Workshop on Content-Based Multimedia Indexing (CBMI), Jun 2014, Klagenfurt, Austria. ⟨hal-01002927⟩

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