EVALUATING THE PRIVACY FEATURES OF PRIVACY PRESERVING MAPS

Abstract

Privacy of images is a growing concern in this day and age. In recent times 3D secure maps offered a solution to hide details but 3D maps the geometry of the scene which leads again to privacy violation. Objects can be detected in the scene and that leads to localization of the objects present in the scene. In this thesis we aim to evaluate these privacy features in a 3D map. Our analysis is to detect objects if found in any map, evaluate its localization and how many instances of same objects can be there in this revealing process. Our Analysis will eventually help in designing more robust privacy features in order to protect privacy.