Blur vs. Block: Investigating the Effectiveness of Privacy-Enhancing Obfuscation for Images

@article{Li2017BlurVB,
  title={Blur vs. Block: Investigating the Effectiveness of Privacy-Enhancing Obfuscation for Images},
  author={Yifang Li and Nishant Vishwamitra and Bart P. Knijnenburg and Hongxin Hu and Kelly Caine},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2017},
  pages={1343-1351}
}
Computer vision can lead to privacy issues such as unauthorized disclosure of private information and identity theft, but it may also be used to preserve user privacy. For example, using computer vision, we may be able to identify sensitive elements of an image and obfuscate those elements thereby protecting private information or identity. However, there is a lack of research investigating the effectiveness of applying obfuscation techniques to parts of images as a privacy enhancing technology… CONTINUE READING

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