HCI and Eye Tracking : Emotion Recognition Using Hidden Markov Model

Abstract

Recognition of Emotion can be identified using Eye Tracking methods which may be non-intrusive. SVD and HMM are used for eye tracking to recognize emotions, which classifies six different emotions with less correlation coefficiency and 77% accuracy is achieved. This work also focus on emotion recognition with HMM using the distance calculation method ,measuring sclera and iris distance.A fully automatic eye tracking system is developed for emotion detection with eye tracking. Face Detection, Feature extraction, Distance Calculation and Emotion classification are developed to recognize emotions. Non intrusive device, webcam is used to capture image, image segmentation algorithm is applied for segmenting the eye parts for emotion analysis. HMM is implemented to classify the emotion with distance calculation method. The proposed algorithm identifies six different emotions with high correlation efficiency

Authors and Affiliations

Rajakumari. B , Senthamarai Selvi. N

Keywords

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  • EP ID EP94970
  • DOI -
  • Views 168
  • Downloads 0

How To Cite

Rajakumari. B, Senthamarai Selvi. N (2015). HCI and Eye Tracking : Emotion Recognition Using Hidden Markov Model. International Journal of Computer Science & Engineering Technology, 6(3), 90-93. https://europub.co.uk/articles/-A-94970