Name
Abstract | ||
|---|---|---|
This paper presents a novel method for facial expression classification that employs the combination of two different feature sets in an ensemble approach. A pool of base classifiers is created using two feature sets: Gabor filters and local binary patterns (LBP). Then a multi-objective genetic algorithm is used to search for the best ensemble using as objective functions the accuracy and the size of the ensemble. The experimental results on two databases have shown the efficiency of the proposed strategy by finding powerful ensembles, which improves the recognition rates between 5% and 10%. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICASSP.2011.5946775 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
emotion recognition,face recognition,genetic algorithms,Gabor filters,LBP,facial expression recognition,local binary patterns,multiobjective genetic algorithm,Emotion recognition,Face recognition | Facial recognition system,Pattern recognition,Facial expression recognition,Computer science,Random subspace method,Local binary patterns,Feature extraction,Facial expression,Artificial intelligence,Ensemble learning,Machine learning,Genetic algorithm | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4577-0537-3 | 978-1-4577-0537-3 | 6 |
PageRank | References | Authors |
0.42 | 14 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thiago H. H. Zavaschi | 1 | 25 | 1.16 |
| Alessandro L. Koerich | 2 | 33 | 9.94 |
| L. S. Oliveira | 3 | 385 | 25.17 |