UPM-3D Facial Expression Recognition Database(UPM-3DFE)

Facial expression studies have now become the central topic among computer vision community; this can be attributed to application it finds in security, human computer interaction, entertainment industries, etc. Using the state of art equipment, We Built a 3D facial expression database named UPM-3DFE database. This database contained 350 face images of 50 persons, with each posing the six universally accepted facial expressions ie; happy, sad, angry, fear, disgust and surprise. The participants are drawn from different ancestral/ethnic background. The database was evaluated using both subjective and objective analysis. We further investigated the relationship between the machine expression recognition and the human effort required to mimic the expression. The result shows a negative correlation.

[1]  Jun Wang,et al.  Static topographic modeling for facial expression recognition and analysis , 2007, Comput. Vis. Image Underst..

[2]  Jun Wang,et al.  A 3D facial expression database for facial behavior research , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[3]  Jörn Ostermann,et al.  Face Animation in MPEG‐4 , 2003 .

[4]  Martti Juhola,et al.  Kernel selection in multi-class support vector machines and its consequence to the number of ties in majority voting method , 2011, Artificial Intelligence Review.

[5]  Ioannis Pitas,et al.  An analysis of facial expression recognition under partial facial image occlusion , 2008, Image Vis. Comput..

[6]  Jun Wang,et al.  3D Facial Expression Recognition Based on Primitive Surface Feature Distribution , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[7]  AbdulRahman M. Baraka,et al.  Impact of Ethnic Group on Human Emotion Recognition Using Backpropagation Neural Network , 2011 .

[8]  Fuhui Long,et al.  Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy , 2003, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Arman Savran,et al.  Bosphorus Database for 3D Face Analysis , 2008, BIOID.

[10]  C. Darwin The Expression of the Emotions in Man and Animals , .

[11]  Miguel Cazorla,et al.  Feature selection, mutual information, and the classification of high-dimensional patterns , 2008, Pattern Analysis and Applications.

[12]  L. Farkas,et al.  Anthropometric Facial Proportions in Medicine , 1986 .

[13]  Anil K. Jain,et al.  Handbook of Face Recognition, 2nd Edition , 2011 .

[14]  Kin-Man Lam,et al.  Facial expression recognition based on shape and texture , 2009, Pattern Recognit..