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A facial gesture switch using hidden Markov models

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I will present a system that can identify a facial gesture based on duration information and optical flow features. There is a short training phase where the user is asked to make his/her gesture three times. A hidden Markov model is then used to identify the signal (gesture) by exploiting the fact that the user made the gesture three times. I will show preliminary results (including an example of a patient with locked-in syndrome using the system). This is still work in progress – suggestions will be more than welcome.

This talk is part of the Inference Group series.

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