Sciweavers

Share
CVPR
2007
IEEE

Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition

10 years 10 months ago
Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition
It is well known that how to extract dynamical features is a key issue for video based face analysis. In this paper, we present a novel approach of facial action units (AU) and expression recognition based on coded dynamical features. In order to capture the dynamical characteristics of facial events, we design the dynamical haar-like features to represent the temporal variations of facial events. Inspired by the binary pattern coding, we further encode the dynamic haar-like features into binary pattern features, which are useful to construct weak classifiers for boosting learning. Finally the Adaboost is performed to learn a set of discriminating coded dynamic features for facial active units and expression recognition. Experiments on the CMU expression database and our own facial AU database show its encouraging performance.
Peng Yang, Qingshan Liu, Dimitris N. Metaxas
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 2007
Where CVPR
Authors Peng Yang, Qingshan Liu, Dimitris N. Metaxas
Comments (0)
books