Scene understanding for identifying persons in TV shows: Beyond face authentication

Our goal is to automatically identify people in TV news and debates without any predefined dictionary of people. In this paper, we focus on the problem of person identification beyond face authentication in order to improve the identification results and not only where the face is detectable. We pro...

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Bibliographic Details
Main Authors: Rouvier, Mickael, Favre, Benoit, Bendris, Meriem, Charlet, Delphine, Damnati, Geraldine
Format: Conference Proceeding
Language:English
Subjects:
Cameras
Face
Feature extraction
Image analysis
Optical character recognition software
Videos
Online Access:Request full text
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Summary:Our goal is to automatically identify people in TV news and debates without any predefined dictionary of people. In this paper, we focus on the problem of person identification beyond face authentication in order to improve the identification results and not only where the face is detectable. We propose to use automatic scene analysis as features for people identification. We exploit two features: scene classification (studio and report) and camera identification. Then, people are identified by propagation strategies of overlaid names (OCR results) and speakers to scene classes and specific camera shots. Experiments performed on the REPERE corpus show improvement of face identification using scene understanding features (+13.9% of F-measure compared to the baseline).
ISSN:1949-3983
1949-3991
DOI:10.1109/CBMI.2014.6849829