基于改进Gabor的手机平台微笑特征提取算法

Wei-guo Yang, Shuo-he Zhen
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引用次数: 3

摘要

随着多年来移动设备的计算机能力和存储能力的增强,将实时微笑识别集成到移动电话和PDA等移动设备中不再是不可实现的。在本文中,我们试图通过在移动设备中提出一种新的用于微笑识别的面部特征提取算法来建立这种可能性。我们使用Gabor滤波器提取全局人脸特征,然后通过AdaBoost算法的训练过程,我们的系统可以有效地在大量特征集中搜索关键特征。最后计算出原始图像中的关键点和相应的卷积掩模。实验结果表明,该算法显著优于几种流行的微笑识别方法,并且大大减少了计算时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel Smile Feature Extraction Algorithm Using Improved Gabor for Mobile Phone Platform
Due to the strengthening of the computer capabilities and storage capacity in mobile devices over the years, an incorporation of real-time smile recognition to mobile devices such as mobile phone and PDA is no longer unattainable. In this paper, we attempt to establish this possibility by presenting a novel face feature extraction algorithm in mobile devices for smile recognition. We extract global face features using Gabor filters, and then through a training process using the AdaBoost algorithm our system can efficiently search for key features in a large set of features. Finally we calculate the key points in the original image and the corresponding convolution masks. Experimental results show that the proposed algorithm significantly outperforms several popular smile recognition methods with a dramatic reduction in computational time.
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