OcrV1, Main, Exploration, bibRecord, 000071

Multiple-View Constrained Clustering For Unsupervised Face Identification In TV-Broadcast

Identifieur interne : 000071 ( Main/Exploration ); précédent : 000070; suivant : 000072

Multiple-View Constrained Clustering For Unsupervised Face Identification In TV-Broadcast

Auteurs : Meriem Bendris [France] ; Delphine Charlet [France] ; Benoit Favre [France] ; Géraldine Damnati [France] ; Rémi Auguste [France]

Source :

RBID : Hal:hal-01194240

Abstract

Our goal is to automatically identify faces in TV broadcast without a pre-defined dictionary of identities. Most methods are based on identity detection (from OCR and ASR) and require a propagation strategy based on visual clustering. In TV content, people appear with many variations making the clustering difficult. In this case, speaker clustering can be a reliable link for face clustering. Multi-modal clustering methods assume a bipartite mapping between modalities. In this paper, we propose to build automatically an incomplete speaker-face mapping based on local evidence of OCR and Lip activity links. Then, we propose schemes of speaker constraints propagation to the face constrained-clustering problem. Experiments performed on the REPERE corpus show an improvement of face identification by propagating names to face clusters (+3.7% F-measure compared to the baseline).

Url:

https://hal-amu.archives-ouvertes.fr/hal-01194240

DOI: 10.1109/ICASSP.2014.6853645

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Hal, to step Corpus: 000086
to stream Hal, to step Curation: 000086
to stream Hal, to step Checkpoint: 000031
to stream Main, to step Merge: 000071
to stream Main, to step Curation: 000071

Le document en format XML

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   |texte=   Multiple-View Constrained Clustering For Unsupervised Face Identification In TV-Broadcast
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Multiple-View Constrained Clustering For Unsupervised Face Identification In TV-Broadcast

Multiple-View Constrained Clustering For Unsupervised Face Identification In TV-Broadcast

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