News browsing system: multimodal analysis

Authors:
Bruno do Nascimento Teixeira;Júlia Epischina Engrácia de Oliveira;Fillipe Dias Moreira de Souza;Tiago Oliveira Cunha;Arnaldo de Albuquerque Araújo;Christiane Okamoto;Lucas Figueiredo;Vinícius de Oliveira Silva;Igor Calil Loures de Oliveira
Affiliations:
Federal University of Minas Gerais, Belo Horizonte, Brazil;Federal University of Minas Gerais, Belo Horizonte, Brazil;Federal University of Minas Gerais, Belo Horizonte, Brazil;Federal University of Minas Gerais, Belo Horizonte, Brazil;Federal University of Minas Gerais, Belo Horizonte, Brazil;Federal University of Minas Gerais, Belo Horizonte, Brazil;Federal University of Minas Gerais, Belo Horizonte, Brazil;Federal University of Minas Gerais, Belo Horizonte, Brazil;Federal University of Minas Gerais, Belo Horizonte, Brazil
Venue:
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Year:
2011

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Abstract

This paper reports a system developed for video browsing based on multimodal analysis. Our multimodal approach performs audio transcription for shot categorization (sports, weather, politics and economy) combining audio and visual information for theme categorization. Its main features include static and dynamic summaries, segmentation using face detection, classification into Indoor/Outdoor scenes based on Support Vector Machine (SVM) and audio transcription for theme keyword search. Keywords are selected to represent the subjects, followed by a simple text search. We conduct a set of experiments for evaluating the effectiveness of the shot subject categorization using audio transcription information.