DocumentCode :
681689
Title :
Robust spontaneous Facial Expression Recognition using Sparse Representation
Author :
Aina, Segun ; Chambers, Jonathon A. ; Phan, Raphael C.-W
Author_Institution :
Adv. Signal Process. Group, Loughborough Univ., Loughborough, UK
fYear :
2013
fDate :
2-3 Dec. 2013
Firstpage :
1
Lastpage :
4
Abstract :
There is very limited literature currently on the use of Sparse Representation (SRC) for the recognition of facial expressions and as far most facial expression analyses; they have been based on posed image databases. These comprise of expressions that often differ from the realistic displays of the expressions that depict affective states. To offer a more practical solution, we apply a recently proposed approach for SRC to the Facial Expression Recognition (FER) problem using the recently developed Natural Visible and Infrared facial Expression (NVIE) database of spontaneous images. We expand the database in order to satisfy the condition of an underdetermined (overcomplete) dictionary and present results showing better recognition rates for spontaneous images than in the existing literature (albeit limited).
Keywords :
face recognition; image classification; image representation; vectors; visual databases; FER problem; NVIE database; SRC; facial expression recognition; natural visible and infrared facial expression database; overcomplete dictionary; posed image databases; sparse representation; spontaneous images; underdetermined dictionary; Affect Detection; Classification; Sparse Representation; Sparsity; Spontaneous Expression Recognition;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Intelligent Signal Processing Conference 2013 (ISP 2013), IET
Conference_Location :
London
Electronic_ISBN :
978-1-84919-774-8
Type :
conf
DOI :
10.1049/cp.2013.2063
Filename :
6740512
Link To Document :
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