Imaging vector fields using line integral convolution
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
The effects of filtered video on awareness and privacy
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Silhouette-Based Human Identification from Body Shape and Gait
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Interactive digital photomontage
ACM SIGGRAPH 2004 Papers
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Preserving Privacy by De-Identifying Face Images
IEEE Transactions on Knowledge and Data Engineering
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Recovering Human Body Configurations Using Pairwise Constraints between Parts
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Recovering 3D Human Body Configurations Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blur filtration fails to preserve privacy for home-based video conferencing
ACM Transactions on Computer-Human Interaction (TOCHI)
Tools for protecting the privacy of specific individuals in video
EURASIP Journal on Applied Signal Processing
Face swapping: automatically replacing faces in photographs
ACM SIGGRAPH 2008 papers
Gender classification in human gait using support vector machine
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Privacy operating characteristic for privacy protection in surveillance applications
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Integrating utility into face de-identification
PET'05 Proceedings of the 5th international conference on Privacy Enhancing Technologies
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Advances in cameras and web technology have made it easy to capture and share large amounts of video data over to a large number of people through services like Google Street View, EveryScape, etc A large number of cameras oversee public and semi-public spaces today These raise concerns on the unintentional and unwarranted invasion of the privacy of individuals caught in the videos To address these concerns, automated methods to de-identify individuals in these videos are necessary De-identification does not aim at destroying all information involving the individuals Its goals are to obscure the identity of the actor without obscuring the action This paper outlines the scenarios in which de-identification is required and the issues brought out by those We also present a preliminary approach to de-identify individuals from videos A bounding box around each individual present in a video is tracked through the video An outline of the individuals is approximated by carrying out segmentation on a 3-D Graph of space-time voxels We explore two de-identification transformations: exponential space-time blur and line integral convolution We show results on a number of public videos and videos collected in a plausible setting We also present the preliminary results of a user-study to validate the effectiveness of the de-identification schemes.