PT Unknown
AU Bogdan Raducanu
   Fadi Dornaika
TI Dynamic Facial Expression Recognition Using Laplacian Eigenmaps-Based Manifold Learning
BT IEEE International Conference on Robotics and Automation
PY 2010
BP 156–161
DI 10.1109/ROBOT.2010.5509290
AB In this paper, we propose an integrated framework for tracking, modelling and recognition of facial expressions. The main contributions are: (i) a view- and texture independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker; (ii) the complexity of the non-linear facial expression space is modelled through a manifold, whose structure is learned using Laplacian Eigenmaps. The projected facial expressions are afterwards recognized based on Nearest Neighbor classifier; (iii) with the proposed approach, we developed an application for an AIBO robot, in which it mirrors the perceived facial expression.
ER