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Face re-identification across pose in thermal infrared spectrum based on local texture descriptors

机译:基于局部纹理描述符的热红外光谱中跨姿势的人脸重新识别

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Face re-identification is a challenging task which is aimed to check similarity of two faces shown in the images. Face recognition system have been investigated since many years mostly in visible domain. We investigate face recognition methods based on facial images acquired in far-infrared range (thermal spectrum). The main reason for using thermal infrared for face recognition is to observe people in night conditions. However, this task is not free of challenges. In this paper we investigate the impact of various head positions on efficiency of face re-identification. The paper presents our measurement approach, results of many series of tests as well as performance metrics of re-identification based on three state-of-the-art facial descriptors.
机译:人脸重新识别是一项具有挑战性的任务,旨在检查图像中显示的两个人脸的相似性。多年来,人脸识别系统主要在可见光领域进行了研究。我们研究基于在远红外范围(热光谱)中获取的面部图像的面部识别方法。使用热红外进行人脸识别的主要原因是在夜间观察人。但是,这项任务并非没有挑战。在本文中,我们研究了各种头部位置对人脸重新识别效率的影响。本文介绍了我们的测量方法,一系列测试的结果以及基于三个最先进的面部描述符的重新识别性能指标。

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