Combining Retrieval and Classification for Real-Time Face Recognition

Giovanni Fusco, Nicoletta Noceti, F. Odone
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引用次数: 7

Abstract

In this paper we propose a real time face recognition method that combines face matching and identity verification modules in a feedback loop, exploiting the temporal efficiency of matching and the performances of SVM classifiers. Our approach represents an ad-hoc solution for settings characterized by variable quantity, quality and distribution of labeled data among the identities. We assess the procedure on two data sets of different complexities, showing the effectiveness of our solution. For its intrinsic peculiarities and its limited computational cost the method finds application in real time systems, and will be implemented on a wearable device for supporting visually impaired people to localize known faces.
结合检索和分类实现实时人脸识别
在本文中,我们提出了一种实时人脸识别方法,它将人脸比对和身份验证模块结合在一个反馈回路中,利用了比对的时间效率和 SVM 分类器的性能。我们的方法是一种临时解决方案,适用于标记数据的数量、质量和身份分布各不相同的情况。我们在两个复杂程度不同的数据集上对该程序进行了评估,显示了我们解决方案的有效性。由于其固有的特殊性和有限的计算成本,该方法可应用于实时系统,并将在支持视障人士定位已知人脸的可穿戴设备上实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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