Person De-identification in Videos

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. 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 ideal 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 an approach to de-identify individuals from videos. Our approach involves tracking and segmenting individuals in a conservative voxel space involving x, y and time. A de-identification transformation is applied per frame using these voxels to obscure the identity. F...

• Type: Conference
• Year: 2009
• Where: ACCV
• Authors: Prachi Agrawal, P. J. Narayanan
• Keywords: ACCV 2009, Computer Vision, Large Number, Semi-public Spaces Today, Share Large Amounts