Adel Lablack

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In this paper, we present an effective method for human action recognition using statistical models based on optical flow orientations. We compute a distribution mixture over motion orientations at each spatial location of the video sequence. The set of estimated distributions constitutes the direction model, which is used as a mid-level feature for the(More)
The determination of the visual field for several persons in a scene is an important problem with many applications in human behavior understanding for security and customized marketing. One such application, addressed in this paper, is to catch the visual field of persons in a scene. We obtained the head pose in the image sequence manually in order to(More)
In this paper, we present an unconstrained visual gaze estimation system. The proposed method extracts the visual field of view of a person looking at a target scene in order to estimate the approximate location of interest (visual gaze). The novelty of the system is the joint use of head pose and eye location information to fine tune the visual gaze(More)
In this paper, we report on user behaviors by analyzing visual clues while users are watching various TV broadcast in pilot settings. We detail the first results of the empathic analysis of viewers watching four distinct videos in dedicated recording sessions. Viewers are sitting in front of a TV set in unconstrained position (free postures, free head poses(More)
The ability to identify users’mental states represents a valuable asset for improving human-computer interaction. Considering that spontaneous emotions are conveyed mostly through facial expressions and the upper Body movements, we propose to use these modalities together for the purpose of negative/positive emotion classification. A method that allows the(More)