Name
Abstract | ||
|---|---|---|
In this paper, the Gabor filter is studied and further expanded for temporal facial expression analysis. Originally, the Gabor feature describes both spatial and frequency characteristics of 2D images. The prominent of the theorem has been validated in research communities for a decade due to its similarity to the human perception system. The performance of the filter in the existing research gives convincing results on recognizing the human emotions by using a still image. However, the previous research neglects the fact that the understanding of human facial expression of emotions is associated by the dynamic relation, which the motion of expression must be witnessed. Therefore, we propose the novel temporal features by deriving the dynamic of Gabor features in the temporal template representations. Then, we decompose the features onto discriminative subspace for estimating the emotion class. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ISM.2014.48 | Multimedia |
Keywords | Field | DocType |
Gabor filters,emotion recognition,face recognition,image classification,image representation,2D images,Gabor filter,dynamic Gabor features,emotion class,expression motion,facial expression classification,human perception system,independent subspace,temporal facial expression analysis,temporal template representations,dynamic Gabor feature,facial expression classification,independent component analysis | Computer science,Gabor filter,Artificial intelligence,Discriminative model,Computer vision,Facial recognition system,Three-dimensional face recognition,Pattern recognition,Subspace topology,Speech recognition,Feature extraction,Facial expression,Independent component analysis | Conference |
Citations | PageRank | References |
1 | 0.36 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Prarinya Siritanawan | 1 | 8 | 2.65 |
| Kazunori Kotani | 2 | 124 | 21.99 |
| Fan Chen | 3 | 49 | 4.80 |