Name
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/NBiS.2013.39 | NBiS |
Keywords | Field | DocType |
still image,bezier curve fitting,emotional recognition,face recognition,human computer interaction,emotion understanding,machine communication system,curve fitting,automatic extraction,emotionally expressive facial image database,facial expression,emotion recognition,emotion extraction,good performance,high importance,expressive facial image database,facial expression analysis,paper present,mobile environment,human emotion,face detection | Facial recognition system,Curve fitting,Pattern recognition,Computer science,Communications system,Feature extraction,Facial expression,Bézier curve,Artificial intelligence,Image database,Face detection | Conference |
ISSN | ISBN | Citations |
2157-0418 | 978-1-4799-2509-4 | 2 |
PageRank | References | Authors |
0.36 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong-Hwan Lee | 1 | 436 | 75.04 |
| Woori Han | 2 | 4 | 1.42 |
| Youngseop Kim | 3 | 12 | 3.52 |