Analyzing KANSEI from facial expressions with fuzzy quantification theory II

Luis A. Diago, Tetsuko Kitaoka, Ichiro Hagiwara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

There is no direct translation for Kansei into English, however the creator of the Kansei Engineering methodology describes Kansei as "the consumer's psychological feeling" towards a product. Here we describe an application where a picture presentation system was applied to define the properties of facial expressions. Instead of analyzing facial expressions of an individual to determine his emotional state, proposed system introduces Fuzzy Quantification Theory II to build a membership function that describes the emotions induced in a subject after the presentation of small set of facial expressions. Using type-II fuzzy quantification theory, the relationship between induced emotions and facial features is linearized by solving a dense generalized eigenvalue problem. As the matrices are ill-conditioned and indefinite, the theory describing the possible solutions of the eigenvalue problem gets complicated. After a generalization of Fix and Heiberger's algorithm is adapted to tackle the problem, facial expressions are sorted on the real number axis and membership functions of two subjects are analyzed.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Fuzzy Systems - Proceedings
Pages1591-1596
Number of pages6
DOIs
Publication statusPublished - 10 Dec 2009
Event2009 IEEE International Conference on Fuzzy Systems - Jeju Island, Korea, Republic of
Duration: 20 Aug 200924 Aug 2009

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2009 IEEE International Conference on Fuzzy Systems
CountryKorea, Republic of
CityJeju Island
Period20/08/0924/08/09

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  • Cite this

    Diago, L. A., Kitaoka, T., & Hagiwara, I. (2009). Analyzing KANSEI from facial expressions with fuzzy quantification theory II. In 2009 IEEE International Conference on Fuzzy Systems - Proceedings (pp. 1591-1596). [5277275] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZY.2009.5277275