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http://dx.doi.org/10.6109/jkiice.2021.25.1.63

CNN Based Face Tracking and Re-identification for Privacy Protection in Video Contents  

Park, TaeMi (Department of Electronics Engineering, Chungbuk University)
Phu, Ninh Phung (Department of Electronics Engineering, Chungbuk University)
Kim, HyungWon (Department of Electronics Engineering, Chungbuk University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.1, 2021 , pp. 63-68 More about this Journal
Abstract
Recently there is sharply increasing interest in watching and creating video contents such as YouTube. However, creating such video contents without privacy protection technique can expose other people in the background in public, which is consequently violating their privacy rights. This paper seeks to remedy these problems and proposes a technique that identifies faces and protecting portrait rights by blurring the face. The key contribution of this paper lies on our deep-learning technique with low detection error and high computation that allow to protect portrait rights in real-time videos. To reduce errors, an efficient tracking algorithm was used in this system with face detection and face recognition algorithm. This paper compares the performance of the proposed system with and without the tracking algorithm. We believe this system can be used wherever the video is used.
Keywords
Face detection; Face recognition; Tracking algorithm; Auto blur system;
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