基于双树复小波变换的多模态表情不变人脸识别

Fazael Ayatollahi, A. Raie, F. Hajati
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引用次数: 2

摘要

提出了一种利用双树复小波变换(DT-CWT)提取人脸刚性和半刚性区域特征的多模态人脸识别方法。DT-CWT将距离和强度图像分解为8个子图像,其中6个带通子图像表示人脸细节,2个低通子图像表示人脸近似。在这项工作中,支持向量机(SVM)被用作分类器。使用包含广泛表情变化的人脸BU-3DFE数据集对所提出的方法进行了评估。在0.1%的误接受率下,总体识别率为98.1%,总体验证率为99.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multimodal expression-invariant face recognition using dual-tree complex wavelet transform
A new multimodal face recognition method which extracts features of rigid and semi-rigid regions of the face using Dual-Tree Complex Wavelet Transform (DT-CWT) is proposed. DT-CWT decomposes range and intensity images into eight sub-images consisting of six band-pass sub-images to represent face details and two low-pass sub-images to represent face approximates. In this work, support vector machine (SVM) has been used as the classifier. The proposed method has been evaluated using the face BU-3DFE dataset containing a wide range of expression changes. Findings include the overall identification rate of 98.1% and the overall verification rate of 99.3% at 0.1% false acceptance rate.
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