A Framework for Fingerprint-Based Detection of Repeating Objects in Multimedia Streams

Sébastien Fenet (1, 2) , Manuel Moussallam (3) , Yves Grenier (1, 2) , Gael Richard (1, 2) , Laurent Daudet (4)

1 S2A - Signal, Statistique et Apprentissage
2 TSI - Département Traitement du Signal et des Images
3 LTCI - Laboratoire Traitement et Communication de l'Information
4 ESPCI Paris - Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris

We present an original framework for the detection of repeating objects in multimedia streams. This framework is designed so that it can work with any fingerprint model. A fingerprint is extracted for each incoming frame of the multimedia stream. The framework then manages this fingerprint so that if one similar frame comes later in the stream, it will be identified as a repetition. The framework has been tested with two distinct fingerprint models on simulated and ’realworld’ data. The results show that the framework performs well with both presented models and that it is suitable for industrial use-cases.

Domains: Signal and Image Processing

Sébastien Fenet, Manuel Moussallam, Yves Grenier, Gael Richard, Laurent Daudet. A Framework for Fingerprint-Based Detection of Repeating Objects in Multimedia Streams. EUSIPCO, Aug 2012, Bucharest, Romania. pp.1464-1468. ⟨hal-00731828⟩