Privacy is a big concern in current video surveillance systems. Due to privacy issues, many strategic places remain unmonitored\r\nleading to security threats. The main problem with existing privacy protection methods is that they assume availability of accurate\r\nregion of interest (RoI) detectors that can detect and hide the privacy sensitive regions such as faces. However, the current detectors\r\nare not fully reliable, leading to breaches in privacy protection. In this paper, we propose a privacy protection method that adopts\r\nadaptive data transformation involving the use of selective obfuscation and global operations to provide robust privacy even\r\nwith unreliable detectors. Further, there are many implicit privacy leakage channels that have not been considered by researchers\r\nfor privacy protection. We block both implicit and explicit channels of privacy leakage. Experimental results show that the\r\nproposed method incurs 38% less distortion of the information needed for surveillance in comparison to earlier methods of\r\nglobal transformation; while still providing near-zero privacy loss.
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