Abstract | ||
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In this paper, color facial expression recognition based on color local features is investigated, in which each color facial image is decomposed into three color component images. For each color component image, we extract a set of color local features to represent the color component image, where color local features could be either color local binary patterns (LBP) or color scale-invariant feature transform (SIFT). To cope with the facial expression recognition problem, we use a group sparse least square regression (GSLSR) model to describe the relationship between the color local feature vectors and the associated emotion label vectors and then perform expression recognition based on it. Finally, experiments on the Multi-PIE color facial expression database are conducted to testify the proposed method and compare the results with state-of-the-art methods. |
Year | DOI | Venue |
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2015 | 10.1109/ICASSP.2015.7178226 | IEEE International Conference on Acoustics, Speech and SP |
Keywords | Field | DocType |
Color facial expression recognition, Group sparse least square regression model, Color local features | Scale-invariant feature transform,Computer vision,HSL and HSV,Facial recognition system,Feature vector,Color histogram,Pattern recognition,Computer science,Local binary patterns,Feature extraction,Artificial intelligence,Color normalization | Conference |
ISSN | Citations | PageRank |
1520-6149 | 2 | 0.38 |
References | Authors | |
12 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Wenming Zheng | 1 | 1240 | 80.70 |
Xiaoyan Zhou | 2 | 2 | 0.38 |
Minghai Xin | 3 | 55 | 5.70 |