Privacy preserving video surveillance using pedestrian tracking mechanism

MiFor '10 Pub Date : 2010-10-29 DOI:10.1145/1877972.1877983
Peng Zhang, Tony Thomas, S. Emmanuel, M. Kankanhalli
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引用次数: 14

Abstract

Video surveillance has become a ubiquitous feature of the modern day life. However, the widespread use of video surveillance has raised concerns about the privacy of people. In this paper, we propose a novel video surveillance with a privacy preserving mechanism. We achieve this by combining the techniques of pedestrian tracking based on a Markov chain with two hidden states, elliptical head contour detection and encryption. The detected pedestrian face/head is obscured by encrypting with a unique key derived from a master key for the privacy preservation purpose. The surveillance video can be viewed with complete privacy or by revoking the privacy of any subset of pedestrians while ensuring complete privacy of the remaining pedestrians.The performance evaluation on many challenging surveillance scenarios shows that the proposed mechanism can effectively and robustly track multiple pedestrians and obscure their faces/head in real time.
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利用行人跟踪机制保护隐私的视频监控
视频监控已经成为现代生活中无处不在的特征。然而,视频监控的广泛使用引发了人们对隐私的担忧。本文提出了一种具有隐私保护机制的新型视频监控系统。我们通过结合基于马尔可夫链的两隐状态行人跟踪、椭圆头轮廓检测和加密技术来实现这一目标。为了保护隐私,使用从主密钥派生的唯一密钥对检测到的行人面部/头部进行加密。监控视频可以在完全隐私的情况下观看,也可以在确保其余行人完全隐私的情况下撤销任何行人子集的隐私。在多个具有挑战性的监控场景下的性能评估表明,该机制能够有效鲁棒地实时跟踪多个行人,并对其面部/头部进行模糊处理。
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When multimedia meets surveillance and forensics in people security Privacy preserving video surveillance using pedestrian tracking mechanism A game-theoretic system security design for the visible watermarking Videntifier" Forensic: large-scale video identification in practice Imputing human descriptions in semantic biometrics
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