Title :
Expression recognition from 3D dynamic faces using robust spatio-temporal shape features
Author :
Le, Vuong ; Tang, Hao ; Huang, Thomas S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
This paper proposes a new method for comparing 3D facial shapes using facial level curves. The pair- and segment-wise distances between the level curves comprise the spatio-temporal features for expression recognition from 3D dynamic faces. The paper further introduces universal background modeling and maximum a posteriori adaptation for hidden Markov models, leading to a decision boundary focus classification algorithm. Both techniques, when combined, yield a high overall recognition accuracy of 92.22% on the BU-4DFE database in our preliminary experiments. Noticeably, our feature extraction method is very efficient, requiring simple preprocessing, and robust to variations of the input data quality.
Keywords :
emotion recognition; face recognition; feature extraction; hidden Markov models; image classification; image segmentation; maximum likelihood estimation; shape recognition; solid modelling; spatiotemporal phenomena; visual databases; 3D dynamic facial shape; BU-4DFE database; decision boundary focus classification algorithm; expression recognition; facial level curve; feature extraction; hidden Markov model; input data quality; maximum a posteriori adaptation; robust spatio-temporal shape features; universal background modeling; Databases; Face recognition; Feature extraction; Hidden Markov models; Markov processes; Shape; Three dimensional displays;
Conference_Titel :
Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
978-1-4244-9140-7
DOI :
10.1109/FG.2011.5771435