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Face recognition using scattering convolutional network

机译:使用散射卷积网络的人脸识别

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Face recognition has been an active research area in the past few decades. In general, face recognition can be very challenging due to variations in viewpoint, illumination, facial expression, etc. Therefore it is essential to extract features which are invariant to some or all of these variations. Here a new image representation, called scattering trans-formetwork, has been used to extract features from faces. The scattering transform is a kind of convolutional network which provides a powerful multi-layer representation for signals. After extraction of scattering features, PCA is applied to reduce the dimensionality of the data and then a multi-class support vector machine is used to perform recognition. The proposed algorithm has been tested on three face datasets and achieved a very high recognition rate.
机译:在过去的几十年中,人脸识别一直是活跃的研究领域。通常,由于视点,照明,面部表情等的变化,面部识别可能会非常具有挑战性。因此,提取对于某些或所有这些变化均不变的特征至关重要。在这里,一种称为散射变换/网络的新图像表示已用于从面部提取特征。散射变换是一种卷积网络,可为信号提供强大的多层表示。提取散射特征后,应用PCA降低数据的维数,然后使用多类支持向量机进行识别。该算法已经在三个人脸数据集上进行了测试,并获得了很高的识别率。

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