Efficient rectangle feature extraction for real-time facial expression recognition based on AdaBoost
Efficient rectangle feature extraction for real-time facial expression recognition based on AdaBoost
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DOI：
10.1109/iros.2005.1545534
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发表时间：
2005-12
期刊：
影响因子：
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通讯作者：
Sung-Uk Jung;Do Hyoung Kim;K. An;M. Chung
中科院分区：
文献类型：
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作者：
Sung-Uk Jung;Do Hyoung Kim;K. An;M. Chung
在本文中，我们提出了一种选择适合面部表情识别的新型矩形特征的方法。本文的基本概念与 Violar 的方法类似，用于人脸检测。我们使用 AdaBoost 算法，在所有可能的矩形类型中选择 3/spl times/3 矩阵形式的矩形特征进行面部表情识别，而不是以前的 Haar 式矩形特征。此外，将由所提出的矩形特征构成的面部表情识别系统与先前的矩形特征的面部表情识别系统的容量进行了比较。结果表明，从仿真和实验结果来看，该方法在面部表情识别方面具有更好的性能。
In this paper, we propose a method of selecting new types of rectangle features that are suitable for facial expression recognition. The basic concept in this paper is similar to Violar's approach, which is used for face detection. Instead of previous Haar-like rectangle features, we choose rectangle features for facial expression recognition among all possible rectangle types in a 3/spl times/3 matrix form using the AdaBoost algorithm. Also, the facial expression recognition system constituted with the proposed rectangle features is compared to that with previous rectangle features with regard to its capacity. The results show that the proposed approach has better performance in facial expression recognition in terms of simulation and experimental results.