A Scalable and Privacy-Aware IoT Service for Live Video Analytics

Junjue Wang, Brandon Amos, Anupam Das, P. Pillai, N. Sadeh, M. Satyanarayanan
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引用次数: 103

Abstract

We present OpenFace, our new open-source face recognition system that approaches state-of-the-art accuracy. Integrating OpenFace with inter-frame tracking, we build RTFace, a mechanism for denaturing video streams that selectively blurs faces according to specified policies at full frame rates. This enables privacy management for live video analytics while providing a secure approach for handling retrospective policy exceptions. Finally, we present a scalable, privacy-aware architecture for large camera networks using RTFace.
用于实时视频分析的可扩展和隐私感知物联网服务
我们介绍OpenFace,我们新的开源人脸识别系统,接近最先进的精度。将OpenFace与帧间跟踪相结合,我们构建了RTFace,这是一种变性视频流的机制,可以根据指定的策略在全帧速率下选择性地模糊人脸。这支持实时视频分析的隐私管理,同时为处理回顾性策略异常提供了一种安全的方法。最后,我们使用RTFace为大型摄像机网络提供了一个可扩展的隐私感知架构。
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