Sylvain Mongy

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The analysis of user behaviors in large video databases is an emergent problem. The growing importance of video in every day life (ex. Movie production) is bound to the importance of video usage. In order to cope with the abundance of available videos, users of these videos need intelligent software systems that fully utilize the rich source information(More)
We study the extraction of characteristics of user behavior in video session encoded as stochastic matrices of finite Markov chain. These behaviors are clustered using a dissimilarity based on the Kullbach-Leibler divergence between probability distributions. The center of each cluster is regarded as the model that generates the behaviors assigned to the(More)
Dans cet article, nous présentons un modèle de fouille des usages de la vidéo pour améliorer la qualité de l'indexation. Nous proposons une approche basée sur un modèle à deux niveaux représentant le comportement des utili-sateurs exploitant un moteur de recherche vidéo. Le premier niveau consiste à modéliser le comportement lors de la lecture d'une vidéo(More)
Our demo focuses on eye tracking on web, image and video data. We use some state-of-the-art measurements, such as scan path, to determine how the user sees web documents, images and videos. Our approach is characterised by automatic eye/gaze tracking with non intrusive sensors, mainly infrared cameras of web, image and video documents. We analyse eye/gaze(More)
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