%0 Conference Proceedings
%T Dynamic Facial Expression Recognition Using Laplacian Eigenmaps-Based Manifold Learning
%A Bogdan Raducanu
%A Fadi Dornaika
%B IEEE International Conference on Robotics and Automation
%D 2010
%@ 1050-4729
%@ 978-1-4244-5038-1
%F Bogdan Raducanu2010
%O OR; MV
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1310), last updated on Wed, 28 Jul 2021 10:06:22 +0200
%X 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.
%U http://dx.doi.org/10.1109/ROBOT.2010.5509290
%P 156–161