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Communication Dans Un Congrès Année : 2014

Affect Recognition Using Magnitude Models of Motion

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The analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, neu-roscience, and related disciplines. We focus on the recognition of the affect state of a single person from video streams. We create a model that allows to estimate the state of four affective dimensions of a person which are arousal, anticipation, power and valence. This sequence model is composed of a magnitude model of motion constructed from a set of point of interest tracked using optical flow. The state of the affective dimension is then predicted using SVM. The experimentation has been performed on a standard dataset and has showed promising results.
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Oussama Hadjerci, Adel Lablack, Ioan Marius Bilasco, Chaabane Djeraba. Affect Recognition Using Magnitude Models of Motion. MultiMedia Modelling 2014, Jan 2014, Dublin, Ireland. pp.339-344, ⟨10.1007/978-3-319-04117-9_33⟩. ⟨hal-00973499⟩
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