Affect-preserving privacy protection of video

Wanxin Xu, Sen Ching Samson Cheung, Neelkamal Soares

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations


The prevalence of wireless networks and the convenience of mobile cameras enable many new video applications other than security and entertainment. From behavioral diagnosis to wellness monitoring, cameras are increasing used for observations in various educational and medical settings. Videos collected for such applications are considered protected health information under privacy laws in many countries. At the same time, there is an increasing need to share such video data across a wide spectrum of stakeholders including professionals, therapists and families facing similar challenges. Visual privacy protection techniques, such as blurring or object removal, can be used to mitigate privacy concern, but they also obliterate important visual cues of affect and social behaviors that are crucial for the target applications. In this paper, we propose a method of manipulating facial expression and body shape to conceal the identity of individuals while preserving the underlying affect states. The experiment results demonstrate the effectiveness of our method.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
Number of pages5
ISBN (Electronic)9781479983391
StatePublished - Dec 9 2015
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: Sep 27 2015Sep 30 2015

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


ConferenceIEEE International Conference on Image Processing, ICIP 2015
CityQuebec City

Bibliographical note

Publisher Copyright:
© 2015 IEEE.


  • Visual privacy protection
  • face image editing
  • linear blend skinning
  • shape deformation

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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