Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/25270
Title: Shot classification and keyframe detection for vision based speakers diarization in parliamentary debates
Authors: Marín Reyes, Pedro Antonio
Lorenzo-Navarro, Javier 
Castrillón-Santana, Modesto 
Sánchez Nielsen, Elena
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Visual diarization
Re-identification
CNN classification
Biometric traits
Issue Date: 2016
Journal: Lecture Notes in Computer Science 
Conference: 17th Conference of the Spanish-Association-for-Artificial-Intelligence (CAEPIA) 
17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016 
Abstract: Automatic labelling of speakers is an essential task for speakers diarization in parliamentary debates given the huge amount of video data to annotate. In this paper, we address the speaker diarization problem as a visual speaker re-identification issue with a special emphasis on the analysis of different shot types. We propose two approaches that makes use of convolutional neural networks (CNN) and biometric traits for keyframe extraction.
URI: http://hdl.handle.net/10553/25270
ISBN: 978-3-319-44635-6
ISSN: 0302-9743
DOI: 10.1007/978-3-319-44636-3_5
Source: Luaces O. et al. (eds) Advances in Artificial Intelligence. CAEPIA 2016. Lecture Notes in Computer Science, vol 9868. Springer, Cham
Appears in Collections:Actas de congresos
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