A perceptual hashing algorithm using latent dirichlet allocation

Authors:
Nicholas Vretos;Nikos Nikolaidis;Ioannis Pitas
Affiliations:
Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece;Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece;Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
Venue:
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Year:
2009

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Abstract

This paper investigates the possibility of extracting latent aspects of a video, using visual information about humans (e.g. actors' faces), in order to develop a fingerprinting (replica detection) framework. We employ a generative probabilistic model, namely Latent Dirichlet Allocation (LDA), so as to capture latent aspects of a video, using facial semantic information derived from the video. We use the bag-of-words concept, (bag-of-faces in our case) in order to ensure exchangeability of the latent variables (e.g. topics). The video topics are modeled as a mixture of distributions of faces in each video. This generative probabilistic model has already been used in the case of text modeling with good results. Experimental results provide evidence that the proposed method performs very efficiently for video fingerprinting.