Yanjia Sun

PhD in Computer Engineering

• Real time Facial Emotion Recognition System
• Facial Emotion Analysis of CEOs to Forecast Firm Performance
• Study on Affective States related Brain Activity

• It has capability of analyzing seven types of basic facial emotions: Anger, Disgust, Fear, Sadness, Happiness, Surprise, and Neutral. It is also used for affect computing.
• For details, please refer to the methodology designed for the system.
• You also can demo the system for your facial videos or others. You will see the result of the facial emotion analysis after uploading your test video clips. Have fun! :)

• A framework is presented to predict the firm performance based on CEO’s facial emotion dynamics during video interviews.
• This is a challenging pattern recognition problem that involves robust detection of various emotional expressions in the uncontrolled environment and classification of spontaneous spatio-temporal data with different personal and biological signature traits.
• The experimental results show the strong and positive reaction of firm performance merely to CEO’s Fear emotion. The findings may contribute to prediction of the market value of firms and actions taken on effective investment.

• A multimodal approach is proposed to jointly evaluate fNIRS signals and EEG signals for affective state detection. Results indicate that proposed method with fNIRS+EEG improves performance over fNIRS or EEG only approaches.
• The methodology involves the simultaneous detection and comparison of various affective expressions by multi-modalities and classification of spatio-temporal data with neural signature traits.