Title
Minor Privacy Protection by Real-time Children Identification and Face Scrambling at the Edge
Abstract
The collection of personal information about individuals, including the minor members of a family, by closedcircuit television (CCTV) cameras creates a lot of privacy concerns. Revealing children’s identifications or activities may compromise their well-being. In this paper, we propose a novel Minor Privacy protection solution using Real-time video processing at the Edge (MiPRE). It is refined to be feasible and accurate to identify minors and apply appropriate privacy-preserving measures accordingly. State of the art deep learning architectures are modified and repurposed to maximize the accuracy of MiPRE. A pipeline extracts face from the input frames and identify minors. Then, a lightweight algorithm scrambles the faces of the minors to anonymize them. Over 20,000 labeled sample points collected from open sources are used for classification. The quantitative experimental results show the superiority of MiPRE with an accuracy of 92.1% with nearreal-time performance.
Year
DOI
Venue
2020
10.4108/eai.13-7-2018.164560
EAI Endorsed Trans. Security Safety
DocType
Volume
Issue
Journal
7
23
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Alem Fitwi100.34
Meng Yuan232.40
Seyed Yahya Nikouei3466.15
Yu Chen482480.54