Multimodal emotion recognition (MER) system

Today, a number of recognition systems have been proposed widely, from audio recognition to image recognition, and from two dimensional databases to three dimensional databases; the study and research on the emotion recognition system become more important than ever before. This paper shows the new research and development of the multimodal emotion recognition system (MER). There are two main categories in this MER System, a new database and the MER fusion recognition part. The MER database and recognition system. The use Microsoft XBOX KINECT sensor, the data include 2D facial images, 3D face feature points and audio wave in a concurrent time based. In the recognition system part, it use multimodal fusion level as final classifier, include decision level fusion, feature level fusion and a new fusion level combination. The MER achieves the best overall and individual emotion recognition that represent the true emotion of human bean.

[1]  Bhusan Chettri,et al.  Nepali Text to Speech Synthesis System using ESNOLA Method of Concatenation , 2013, International Journal of Computer Applications.

[2]  M Murugappan,et al.  Physiological signals based human emotion Recognition: a review , 2011, 2011 IEEE 7th International Colloquium on Signal Processing and its Applications.

[3]  Shipeng Li,et al.  Kinect-Like Depth Data Compression , 2013, IEEE Transactions on Multimedia.

[4]  Ling Guan,et al.  A Deformable 3-D Facial Expression Model for Dynamic Human Emotional State Recognition , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  Shiqi Wang,et al.  Kinect-Like Depth Compression with 2D+T Prediction , 2012, 2012 IEEE International Conference on Multimedia and Expo Workshops.

[6]  Ling Guan,et al.  Recognizing human emotion from audiovisual information , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[7]  Stan Z. Li,et al.  2D–3D face matching using CCA , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

[8]  P. Ekman,et al.  Strong evidence for universals in facial expressions: a reply to Russell's mistaken critique. , 1994, Psychological bulletin.