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Multispectral Texture Features from Visible and Near-Infrared Synthetic Face Images for Face Recognition

机译:可见光和近红外合成人脸图像的多光谱纹理特征用于人脸识别

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Recently, high-performance face recognition has attracted research attention in real-world scenarios. Thanks to the advances in sensor technology, face recognition system equipped with multiple sensors has been widely researched. Among them, face recognition system with near-infrared imagery has been one important research topic. In this paper, complementary effect resided in face images captured by nearinfrared and visible rays is exploited by combining two distinct spectral images (i.e., face images captured by near-infrared and visible rays). We propose a new texture feature (i.e., multispectral texture feature) extraction method with synthesized face images to achieve high-performance face recognition with illumination-invariant property. The experimental results show that the proposed method enhances the discriminative power of features thanks the complementary effect.
机译:近年来,高性能人脸识别在现实世界中引起了研究关注。由于传感器技术的进步,配备了多个传感器的面部识别系统得到了广泛的研究。其中,具有近红外图像的人脸识别系统已经成为重要的研究课题之一。在本文中,通过组合两个不同的光谱图像(即,由近红外和可见光捕获的面部图像)来利用由近红外和可见光捕获的面部图像中存在的互补效应。我们提出了一种新的具有合成人脸图像的纹理特征(即多光谱纹理特征)提取方法,以实现具有照明不变性的高性能人脸识别。实验结果表明,该方法具有互补作用,增强了特征的判别能力。

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