Privacy enabled video surveillance using a two state Markov tracking algorithm |
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Authors: | Peng Zhang Tony Thomas Sabu Emmanuel |
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Affiliation: | (1) School of Computer Engineering, Nanyang Technological University, Singapore, Singapore |
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Abstract: | Nowadays video surveillance systems are widely deployed in many public places. However, the widespread use of video surveillance
violates the privacy rights of the people. Many authors have addressed the privacy issues from various points of view. In
this paper we propose a novel, on-demand selectively revocable, privacy preserving mechanism. The surveillance video can be
tuned to view with complete privacy or by revoking the privacy of any subset of pedestrians while ensuring complete privacy
to the remaining pedestrians. We achieve this by tracking the pedestrians using a novel Markov chain algorithm with two hidden
states, detecting the head contour of the tracked pedestrians and obscuring their faces using an encryption mechanism. The
detected pedestrian face/head is obscured by encrypting with a unique key derived from a master key for the privacy preservation
purpose. The performance evaluations on many challenging surveillance scenarios show that the proposed mechanism can effectively
and robustly track as well as identify multiple pedestrians and obscure/unobscure their faces/head in real time. |
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