Deep learning based face recognition system with smart glasses

O. Daescu, Hongyao Huang, Maxwell Weinzierl
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引用次数: 6

Abstract

Individuals with prosopagnosia have difficulty in identifying different people by their faces. Our goal is to design and develop a face recognition system with wearable glasses to recognize faces and provide identity information to users. Unlike other existing systems that run locally on glasses or cellphones, we introduce a client-server architecture system for facial identification. We designed and implemented applications both on a pair of smart glasses and a cellphone to capture images and communicate with the server. Deep Convolutional Neural Networks (CNN) were chosen to build our face recognition on the back-end system and we achieved 98.18% accuracy for face recognition. The system is designed to handle new identities and new faces without having to rebuild the model.
基于深度学习的智能眼镜人脸识别系统
患有面孔失认症的人很难通过面部识别不同的人。我们的目标是设计和开发一个带有可穿戴眼镜的人脸识别系统,以识别人脸并为用户提供身份信息。与其他现有的在眼镜或手机上本地运行的系统不同,我们引入了一个客户端-服务器架构的面部识别系统。我们在一副智能眼镜和一部手机上设计并实现了应用程序,用于捕获图像并与服务器通信。后端系统选择深度卷积神经网络(CNN)构建人脸识别,人脸识别准确率达到98.18%。该系统旨在处理新身份和新面孔,而无需重建模型。
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