Robust spontaneous facial expression recognition using sparse representation

Segun Aina, Jonathon A. Chambers, Raphael C.W. Phan

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)


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).

Original languageEnglish
Title of host publicationIET Intelligent Signal Processing Conference 2013, ISP 2013
Edition619 CP
Publication statusPublished - 2013
Externally publishedYes
EventIET Intelligent Signal Processing Conference 2013 - London, United Kingdom
Duration: 2 Dec 20133 Dec 2013 (Proceedings)

Publication series

NameIET Conference Publications
Number619 CP


ConferenceIET Intelligent Signal Processing Conference 2013
Abbreviated titleISP 2013
CountryUnited Kingdom
Internet address


  • Affect detection
  • Classification
  • Sparse representation
  • Sparsity
  • Spontaneous expression recognition

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