Monday, 19 October 2015
The scope of the project is on an image classification framework for image categories which may be associated with similar policies, and on a policy prediction algorithm to automatically generate a policy for each newly uploaded image, also according to users’ social features.
There is a large body of work on image content analysis, for classification and interpretation retrieval and photo ranking also in the context of online photo sharing sites. Of these works, existing work is probably the closest to ours. The existing system explores privacy-aware image classification using a mixed set of features, both content and meta-data.
· This is however a binary classification (private versus public), so the classification task is very different than ours.
· Existing proposals for automating privacy settings appear to be inadequate to address the unique privacy needs of images due to the amount of information implicitly carried within images, and their relationship with the online environment wherein they are exposed.
· Users struggle to set up and maintain privacy settings in the most content sharing websites.
· The impact of social environment and personal characteristics.
· The role of image’s content and metadata.
The A3P system provides a comprehensive framework to infer privacy preferences based on the information available for a given user. A3P also effectively tackled the issue of cold-start, leveraging social context information. This project proves that our A3P is a practical tool that offers significant improvements over current approaches to privacy.
· Speed - 1.1 Ghz
· RAM - 256 MB(min)
· Hard Disk - 20 GB
· Floppy Drive - 1.44 MB
· Key Board - Standard Windows Keyboard
· Mouse - Two or Three Button Mouse
· Monitor - SVGA
· Operating System : Windows 7
· Front End : JSP AND SERVLET
· Database : MYSQL