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Fusing Iris and Periocular Region for User Verification in Head Mounted Displays

机译:融合虹膜和眼周区域以便在头戴式显示器中进行用户验证

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The growing popularity of Virtual Reality and Augmented Reality (VR/AR) devices in many applications also demands authentication of users. As the devices inherently capture the eye image while capturing the user interaction, the authentication can be devised using the iris and periocular recognition. While both iris and periocular data being non-ideal unlike the data captured from standard biometric sensors, the authentication performance is expected to be lower. In this work, we present and evaluate a fusion framework for improving the biometric authentication performance. Specifically, we employ score-level fusion for two independent biometric systems of iris and periocular region to avoid expensive feature-level fusion. With a detailed evaluation of three different score-level fusion after the score normalization on a dataset of 12579 images, we report the performance gain in authentication using score-level fusion for iris and periocular recognition.
机译:虚拟现实和增强现实(VR / AR)设备在许多应用中的日益普及也要求对用户进行身份验证。由于设备在捕获用户交互时固有地捕获了眼睛图像,因此可以使用虹膜和眼周识别来设计身份验证。尽管虹膜和眼周数据都是不理想的,这与从标准生物特征传感器捕获的数据不同,但认证性能预计会较低。在这项工作中,我们提出并评估了一种融合框架,以改善生物特征认证性能。具体来说,我们对虹膜和眼周区域的两个独立生物特征识别系统采用分数级融合,以避免昂贵的特征级融合。在对12579张图像的数据集进行分数归一化后,对三种不同的分数级融合进行了详细的评估,我们报告了使用分数级融合进行虹膜和眼周识别的身份验证性能。

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