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automatic analysis may have many applications such as smart human-computer interactions or multimedia indexing. Main difficulties for an efficient speech emotion classification reside in complex emotional class borders leading to necessity of appropriate audio feature selection. While current work in the literature only relies on classical frequency and(More)
3D face landmarking aims at automatic localization of 3D facial features and has a wide range of applications, including face recognition, face tracking, facial expression analysis. Methods so far developed for pure 2D texture images were shown sensitive to lighting condition changes. In this paper, we present a statistical model-based technique for(More)
Evaluating the performance of computer vision algorithms is classically done by reporting classification error or accuracy, if the problem at hand is the classification of an object in an image, the recognition of an activity in a video or the categorization and labeling of the image or video. If in addition the detection of an item in an image or a video,(More)
Textured 3D face models capture precise facial surfaces along with the associated textures, making it possible for an accurate description of facial activities. In this paper, we present a unified probabilistic framework based on a novel Bayesian Belief Network (BBN) for 3D facial expression and Action Unit (AU) recognition. The proposed BBN performs(More)
We investigate the role that geometric, tex-tual and visual features play in the task of predicting a preposition that links two visual entities depicted in an image. The task is an important part of the subsequent process of generating image descriptions. We explore the prediction of prepositions for a pair of entities, both in the case when the labels of(More)
Visual object recognition is one of the most challenging problems in computer vision, due to both inter-class and intra-class variations. The local appearance-based features, especially SIFT, have gained a big success in such a task because of their great discriminative power. In this paper, we propose to adopt two different kinds of feature to characterize(More)
On one hand, the fact that Galvanic Skin Response (GSR) is highly correlated with the user affective arousal provides the possibility to apply GSR in emotion detection. On the other hand, temporal correlation of real-time GSR and self-assessment of arousal has not been well studied. This paper confronts two modalities representing the induced emotion when(More)
We describe the LIRIS human activities dataset, the dataset used for the ICPR 2012 human activities recognition and localization competition. In contrast to previous competitions and existing datasets, the tasks focus on complex human behavior involving several people in the video at the same time, on actions involving several interacting people and on(More)