Emotional Recognition from Facial Expression Analysis Using Bezier Curve Fitting

Author

Yong-Hwan Lee ; Woori Han ; Youngseop Kim

Author_Institution

Dept. of Appl. Comput. Eng., Dankook Univ., Yongin, South Korea

fYear

2013

fDate

4-6 Sept. 2013

Firstpage

250

Lastpage

254

Abstract

Extracting and understanding of emotion is of high importance for the interaction among human and machine communication systems. The most expressive way to display the human´s emotion is through facial expression analysis. This paper presents and implements an automatic extraction and recognition method of facial expression and emotion from still image. To evaluate the performance of the proposed algorithm, we assess the ratio of success with emotionally expressive facial image database. Experimental results shows average 66% of success to analyze and recognize the facial expression and emotion. The obtained result indicates the good performance and enough to applicable to mobile environments.

Keywords

curve fitting; emotion recognition; face recognition; human computer interaction; Bezier curve fitting; emotion extraction; emotion understanding; emotional recognition; emotionally expressive facial image database; facial expression analysis; human emotion; machine communication system; mobile environment; still image; Databases; Emotion recognition; Face; Face recognition; Feature extraction; Image color analysis; Skin; Bezier Curve Fitting; Emotional Recognition; Face Detection; Facial Expression Analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Network-Based Information Systems (NBiS), 2013 16th International Conference on

Conference_Location

Gwangju

Print_ISBN

978-1-4799-2509-4

Type

conf

DOI

10.1109/NBiS.2013.39

Filename

6685404