Title
Spontaneous versus posed smile recognition using discriminative local spatial-temporal descriptors
Abstract
Automatic recognition of spontaneous versus posed (SVP) facial expressions has received widespread attention in recent years for its potential applications in friendly human machine interface. Most existing works of SVP facial expression recognition extract geometry-based features which heavily rely on accurate detection and tracking of facial feature points. In this paper, a novel approach is proposed to distinguish between spontaneous and posed smiles using discriminative completed LBP from three orthogonal planes, which is an appearance-based local spatial-temporal descriptor. The descriptor devotes to extracting most robust and discriminative patterns of interest. In addition, flexible facial subregion cropping, a spatial division method, is proposed taking into account different facial organ size of different people and filtering of redundant information. Besides, in the temporal domain, a new division method is also applied, which divides the smile process according to smile dynamics. Experiments on three benchmark databases and comparisons to the state-of-the-art methods validate the advantages of our approach, obtaining an accuracy rate of 91.40%. © 2014 IEEE.
Year
DOI
Venue
2014
10.1109/ICASSP.2014.6853795
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Keywords
DocType
ISSN
LBP,Smile Recognition,Spontaneous versus Posed
Conference
15206149
ISBN
Citations 
PageRank 
9781479928927
7
0.49
References 
Authors
9
3
Name
Order
Citations
PageRank
Wu Pingping1324.36
Hong Liu274782.65
Xue-Wu Zhang34311.98