PT Journal
AU Bogdan Raducanu
   Fadi Dornaika
TI Texture-independent recognition of facial expressions in image snapshots and videos
SO Machine Vision and Applications
JI MVA
PY 2013
BP 811
EP 820
VL 24
IS 4
DI 10.1007/s00138-012-0447-z
AB This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines.
ER