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Comparison of Two Methods for Unsupervised Person Identification in TV Shows
Type of publication: Conference paper
Citation: Gay_CBMI_2014
Publication status: Published
Booktitle: 12th International Workshop on Content-Based Multimedia Indexing
Year: 2014
Abstract: We address the task of identifying people appearing in TV shows. The target persons are all people whose identity is said or written, like the journalists and the well known people, as politicians, athletes, celebrities, etc. In our approach, overlaid names displayed on the images are used to identify the persons without any use of biometric models for the speakers and the faces. Two identification methods are evaluated as part of the REPERE French evaluation campaign. The first one relies on co-occurrence times between overlay person names and speaker/face clusters, and rule-based decisions which assign a name to each monomodal cluster. The second method uses a Conditionnal Random Field (CRF) which combine different types of co-occurrence statistics and pair-wised constraints to jointly identify speakers and faces.
Keywords: Content-based multimedia indexing, Face dirarization, person diarization
Projects Idiap
Authors Gay, Paul
Dupuy, Gregor
Odobez, Jean-Marc
Meignier, Sylvain
Deleglise, Paul
Added by: [UNK]
Total mark: 0
  • Gay_CBMI_2014.pdf