Enabling Live Video Analytics with a Scalable and Privacy-Aware Framework.

TOMCCAP(2018)

引用 47|浏览157
暂无评分
摘要
We show how to build the components of a privacy-aware, live video analytics ecosystem from the bottom up, starting with OpenFace, our new open-source face recognition system that approaches state-of-the-art accuracy. Integrating OpenFace with interframe 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 and show how it can be an enabler for a vibrant ecosystem and marketplace of privacy-aware video streams and analytics services.
更多
查看译文
关键词
Privacy mediator, cloud computing, cloudlet, edge computing, face recognition
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要