PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Facial Expression Recognition Using Nonrigid Motion Parameters and Shape-from-Shading
Fang Liu, Edwin Hancock and Will Smith
In: Computer Analysis of Images and Patterns - 14th International Conference, CAIP 2011, August 29-31, 2011, Seville, Spain.


This paper presents a 3D motion based approach to facial expression recognition from video sequences. A non-Lambertian shape-from-shading (SFS) framework is used to recover 3D facial surfaces. The SFS technique avoids heavy computational requirements normally encountered by using a 3D face model. Then, a parametric motion model and optical flow are employed to obtain the nonrigid motion parameters of surface patches. At first, we obtain uniform motion parameters under the assumptions that motion due to change in expressions is temporally consistent. Then we relax the uniform motion constraint, and obtain temporal motion parameters. The two types of motion parameters are used to train and classify using Adaboost and HMM-based classifier. Experimental results show that temporal motion parameters perform much better than uniform motion parameters, and can be used to efficiently recognize facial expression.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:8555
Deposited By:Edwin Hancock
Deposited On:13 February 2012