Image-based stress recognition from a model-based face tracking system
نویسنده
چکیده
This paper presents a comparison of learning methods to detect stress from video sequences of people with a close-up of their face. The video sequences consist of people subjected to various psychological tests that induce high and low stress situations. We use a model-based tracking system to get the face movements and deformations in a parameterized form. We compare different learning methods to learn from these parameters to do recognition of high and low stress situations for labeled video sequences. We will present results of using Hidden Markov Models (HMMs) for recognition. The main contribution of this paper is a novel method of stress detection from image sequences of a person’s face.
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