Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-34778-8_37
Title: A multimodal approach for online estimation of subtle facial expression
Authors: Xiang, X.
Kankanhalli, M.S. 
Keywords: eye pupil
online
subtle facial expression
Issue Date: 2012
Source: Xiang, X.,Kankanhalli, M.S. (2012). A multimodal approach for online estimation of subtle facial expression. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7674 LNCS : 402-413. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-34778-8_37
Abstract: Recognizing subtle emotional expression of human is a challenging and interesting problem in the field of human computer interaction. Multimodality is a prospective way to help solve this problem. Therefore, in this paper, we first take advantage of a novel "sparse representation" approach to compute the matching degree of current facial expression to each basic emotion class. Concurrently, we also use an eye tracker to obtain the instant pupillary response, which gives us clues to the subtle emotion. We combine the results of facial expression and pupillary information, take into account the previous emotional state to classify the current subtle emotional expression. Finally, a Markov Model is used to compute a directed graph to model the changes of human's emotion. The experimental results show that: First, the sparse representation has a good classification rate on facial expression; Second, the fusion of facial expression, pupillary size and previous emotional state is a promising strategy for analyzing subtle expression. © 2012 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/41252
ISBN: 9783642347771
ISSN: 03029743
DOI: 10.1007/978-3-642-34778-8_37
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

1
checked on Dec 13, 2017

Page view(s)

80
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.