Facial expression preserving privacy protection using image melding

An enormous number of images are currently shared through social networking services such as Facebook. These images usually contain appearance of people and may violate the people's privacy if they are published without permission from each person. To remedy this privacy concern, visual privacy protection, such as blurring, is applied to facial regions of people without permission. However, in addition to image quality degradation, this may spoil the context of the image: If some people are filtered while the others are not, missing facial expression makes comprehension of the image difficult. This paper proposes an image melding-based method that modifies facial regions in a visually unintrusive way with preserving facial expression. Our experimental results demonstrated that the proposed method can retain facial expression while protecting privacy.

[1]  Jianping Fan,et al.  Automatically protecting privacy in consumer generated videos using intended human object detector , 2010, ACM Multimedia.

[2]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Touradj Ebrahimi,et al.  Using face morphing to protect privacy , 2013, 2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance.

[4]  Bradley Malin,et al.  Preserving privacy by de-identifying face images , 2005, IEEE Transactions on Knowledge and Data Engineering.

[5]  Marco Zennaro,et al.  Large-scale privacy protection in Google Street View , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[6]  Touradj Ebrahimi,et al.  H.264/AVC video scrambling for privacy protection , 2008, 2008 15th IEEE International Conference on Image Processing.

[7]  Mohan S. Kankanhalli,et al.  Privacy aware publication of surveillance video , 2013, Int. J. Trust. Manag. Comput. Commun..

[8]  Eli Shechtman,et al.  Image melding , 2012, ACM Trans. Graph..

[9]  Noboru Babaguchi,et al.  Privacy protecting visual processing for secure video surveillance , 2008, 2008 15th IEEE International Conference on Image Processing.

[10]  Sharath Pankanti,et al.  Enabling video privacy through computer vision , 2005, IEEE Security & Privacy Magazine.

[11]  Mohan S. Kankanhalli,et al.  W3-privacy: understanding what, when, and where inference channels in multi-camera surveillance video , 2012, Multimedia Tools and Applications.

[12]  Jianping Fan,et al.  Constructing Distributed Hippocratic Video Databases for Privacy-Preserving Online Patient Training and Counseling , 2009, IEEE Transactions on Information Technology in Biomedicine.

[13]  Andrew Blake,et al.  "GrabCut" , 2004, ACM Trans. Graph..

[14]  Luc Van Gool,et al.  Real-time facial feature detection using conditional regression forests , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[15]  Nalini Venkatasubramanian,et al.  Privacy protecting data collection in media spaces , 2004, MULTIMEDIA '04.

[16]  Jack Brassil,et al.  Technical Challenges in Location-Aware Video Surveillance Privacy , 2009, Protecting Privacy in Video Surveillance.

[17]  Kazuaki Tanaka,et al.  Motion is enough: How real-time avatars improve distant communication , 2013, 2013 International Conference on Collaboration Technologies and Systems (CTS).

[18]  Serge J. Belongie,et al.  Removing pedestrians from Google street view images , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.