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Image-based stress recognition from a model-based tracking system

Image-based stress recognition from a model-based tracking system. Sundara Venkataraman (sundara@paul). Motivation. Stress recognition from faces has a lot of applications Human-computer Interaction Security Problem has not been explored

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Image-based stress recognition from a model-based tracking system

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  1. Image-based stress recognition from a model-based tracking system Sundara Venkataraman (sundara@paul)

  2. Motivation • Stress recognition from faces has a lot of applications • Human-computer Interaction • Security • Problem has not been explored • Our approach : Tracking faces + recognition from tracking data

  3. Face Tracking • Generic face model is fit to a given subject’s face • Involves marking out the contour, eyes, nose and mouth • Each of these parts are fit separately to get an accurate fit of • a subject’s face • Model incorporates framework for eyebrow movements, lip • deformations and jaw movements

  4. Face Tracking • Tracking is based on statistical cue integration • Cues are edges, point trackers and optical flow • The cues are integrated statistically using a maximum • likelihood estimation

  5. Stress Recognition • Training/Testing data • Tracking data for about 13 subjects with high/low stress • situations were used for training/recognition • Used HTK for HMM training and testing • Issues in using Dynamic Bayesian Network with BNT

  6. Results • 5 states in the HMM for both data splits • 75% - 25 % split between training and test data • gave 100% recognition. • 50% - 50% split between training and test data • gave 92 % recognition accuracy.

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