Name
Abstract | ||
|---|---|---|
Facial expression analysis is essential to enable socially intelligent processing of multimedia video content. Most facial expression recognition algorithms generally analyze the whole image sequence of an expression to exploit its temporal characteristics. However, it is seldom studied whether it is necessary to utilize all the frames of a sequence, since human beings are able to capture the dynamics of facial expressions from very short sequences (even only one frame). In this paper, we investigate the impact of the number of frames in a facial expression sequence on facial expression recognition accuracy. In particular, we develop a key frame selection method through key point based frame representation. Experimental results on the popular CK facial expression dataset indicate that recognition accuracy achieved with half of the sequence frames is comparable to that of utilizing all the sequence frames. Our key frame selection method can further reduce the number of frames without clearly compromising recognition accuracy. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICMEW.2012.56 | ICME Workshops |
Keywords | Field | DocType |
facial expression recognition require,recognition accuracy,key frame selection method,facial expression,facial expression analysis,popular ck facial expression,facial expression recognition accuracy,short sequence,facial expression sequence,facial expression recognition,sequence frame,image recognition,social sciences,face,face recognition,support vector machines,accuracy | Facial recognition system,Computer vision,Facial expression recognition,Three-dimensional face recognition,Pattern recognition,Computer science,Support vector machine,Exploit,Facial expression,Artificial intelligence,Key frame,Image sequence | Conference |
ISSN | Citations | PageRank |
2330-7927 | 1 | 0.35 |
References | Authors | |
10 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kaimin Yu | 1 | 55 | 4.54 |
| Zhiyong Wang | 2 | 550 | 51.76 |
| Genliang Guan | 3 | 180 | 8.23 |
| Qiuxia Wu | 4 | 103 | 9.25 |
| Zheru Chi | 5 | 910 | 79.37 |
| David Dagan Feng | 6 | 3329 | 413.76 |