By Topic

Hierarchical multistream recognition of facial expressions

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chibelushi, C.C. ; Sch. of Comput., Staffordshire Univ., Stafford, UK ; Bourel, F.

Achieving optimal recognition accuracy, particularly under conditions of input data variability, is a challenge for automatic facial expression recognition. However, little research has been devoted to investigating the robustness of automatic expression recognition under adverse conditions. A facial expression modelling approach is proposed for enhancing the robustness of expression recognition. The approach is founded on hierarchical state-based modelling of streams that represent spatially localised expression dynamics. Experimental assessment shows that the proposed model achieves high and stable recognition accuracy over a range of input data degradation. Moreover, interstream coupling as well as the inclusion of adaptive estimation of model reliability and credibility are shown to make a positive contribution to recognition accuracy.

Published in:

Vision, Image and Signal Processing, IEE Proceedings -  (Volume:151 ,  Issue: 4 )