상세정보
학술대회
A Privacy-Preserving Human Tracking Scheme in Centralized Cloud based Camera Networks
- 저자
- Yu-Chi Chen, Chun-Te Chu, Jenq-Neng Hwang, 유장희
- 발행일
- 201406
- 출처
- International Conference on Communications (ICC) 2014, pp.793-798
- 협약과제
- 13VS1100, 사람에 의한 안전위협의 실시간 인지를 위한 능동형 영상보안 서비스용 원거리 (CCTV 주간환경 5m이상) 사람 식별 및 검색 원천기술 개발, 유장희
- 초록
- Camera networks have been deployed to facilitate human tracking across multi-cameras in the modern surveillance systems. However, human privacy is an important concern on security surveillance. More specifically, in the real world, surveillance cameras are commonly installed by different entities (such as departments or companies), and any recorded video by one entity should not be shared with others to protect the privacy of tracked humans, while maintaining the knowledge of those moving trajectories of tracked humans in a centralized cloud server. This tracking across multi-cameras information can serve as a very powerful analysis tool for locating crime suspects or collecting business statistics. This paper is the first to aim at the importance of privacy-preserving in a multiple-camera tracking system. We address the problems of privacy-preserving human tracking based on Paillier encryption without revealing any recorded video or data, and introduce the secure multiple-camera system which consists of two stages: training and testing stages. Finally, the security analyses and simulations show the effectiveness of the proposed scheme. © 2014 IEEE.
- KSP 제안 키워드
- Business statistics, Camera Networks, Camera system, Cloud server, Cloud-based, Human tracking, Multi-camera, Privacy-preserving, Real-world, Surveillance system, Tracking System