@inproceedings{d3a8a4770e0b4feb9c0571bce6e47a59,
title = "A novel feature extraction method using pyramid histogram of orientation gradients for smile recognition",
abstract = "Recognizing smiles is of much importance for detecting happy moods. Gabor features are conventionally widely applied to facial expression recognition, but the number of Gabor features is usually too large. We proposed to use Pyramid Histogram of Oriented Gradients (PHOG) as the features extracted for smile recognition in this paper. The comparisons between the PHOG and Gabor features using a publicly available dataset demonstrated that the PHOG with a significantly shorter vector length could achieve as high a recognition rate as the Gabor features did. Furthermore, the feature selection conducted by an AdaBoost algorithm was not needed when using the PHOG features. To further improve the recognition performance, we combined these two feature extraction methods and achieved the best smile recognition rate, indicating a good value of the PHOG features for smile recognitions.",
keywords = "AdaBoost, Gabor feature, Pyramid histogram of oriented gradients, Smile recognition, Support vector machine",
author = "Yang Bai and Lihua Guo and Lianwen Jin and Qinghua Huang",
year = "2009",
doi = "10.1109/ICIP.2009.5413938",
language = "英语",
isbn = "9781424456543",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "3305--3308",
booktitle = "2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings",
note = "2009 IEEE International Conference on Image Processing, ICIP 2009 ; Conference date: 07-11-2009 Through 10-11-2009",
}