Abstract
A fully automated, multi-stage architecture for emotion recognition is presented. Faces are located using a tracker based upon the ratio template algorithm [1]. Optical flow of the face is subsequently determined using a multi-channel gradient model [2]. The speed and direction information produced is then averaged over different parts of the face and ratios taken to determine how facial parts are moving relative to one another. This information is entered into multi-layer perceptrons trained using back propagation. The system then allocates any facial expression to one of four categories, happiness, sadness, surprise, or disgust. The three key stages of the architecture are all inspired by biological systems. This emotion recognition system runs in real-time and has a range of applications in the field of humancomputer interaction.
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Anderson, K., McOwan, P.W. (2003). Real-Time Emotion Recognition Using Biologically Inspired Models. In: Kittler, J., Nixon, M.S. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2003. Lecture Notes in Computer Science, vol 2688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44887-X_15
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DOI: https://doi.org/10.1007/3-540-44887-X_15
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