Image Processing Reference
A local feature-based facial
expression recognition system
from depth video
Md. Zia Uddin Department of Computer Education, Sungkyunkwan University, Seoul, Republic of Korea
In this chapter, a novel approach is proposed to recognize some facial expressions from time-sequential
depth videos. Local directional patern features are extracted from the time-sequential depth faces that
are followed by principal component analysis and linear discriminant analysis to make the features more
robust. Finally, the local features are applied with hidden Markov models to model and recognize difer-
ent facial expressions successfully. The proposed approach shows superior recognition rate against the
This work was supported by Faculty Research Fund, Sungkyunkwan University, 2013.
Facial expression recognition (FER) provides machines a way of sensing emotions that can be
considered one of the mostly used artiicial intelligence and patern analysis applications [ 1 - 10 ] .
In case of extracting peoples' expression images through Red Green Blue (RGB) cameras, most