The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
The effects of filtered video on awareness and privacy
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Novel Broadband Ultrasonic Location System
UbiComp '02 Proceedings of the 4th international conference on Ubiquitous Computing
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Preserving Privacy by De-Identifying Face Images
IEEE Transactions on Knowledge and Data Engineering
A relative positioning system for co-located mobile devices
Proceedings of the 3rd international conference on Mobile systems, applications, and services
The Ubiquitous Camera: An In-Depth Study of Camera Phone Use
IEEE Pervasive Computing
Towards context-aware face recognition
Proceedings of the 13th annual ACM international conference on Multimedia
Model-Based Face De-Identification
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
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Today's high-end mobile phones commonly include one or two digital cameras. These devices, also known as cameraphones, allow their owners to take photographs anywhere, at any time with practically no cost. As a result, many urban dwellers are photographed everyday without even being aware of it. Although in many countries, legislation recognises the right of people to veto the dissemination of their image, snapshots including recognisable passers-by often end up on photo-sharing websites. In this paper, we present a cooperative system for cameraphones which automatically anonymises faces of people photographed involuntarily. Our system, called BlurMe, uses Bluetooth awareness to inform a photographer's cameraphone when people around this photographer do not wish for their picture being taken. It then identifies subjects on the photograph and anonymises other people's faces. BlurMe was tested on 876 face regions detected on 150 real-life photographs collected from a photo-sharing website and manually labelled for subject faces. The system achieved very promising results on photographs with up to three subjects.