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    FOREGROUND AND SCENE STRUCTURE PRESERVED VISUAL PRIVACY PROTECTION USING DEPTH INFORMATION

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    Genre
    Thesis/Dissertation
    Date
    2014
    Author
    Elezovikj, Semir
    Advisor
    Ling, Haibin
    Department
    Computer and Information Science
    Subject
    Computer Science
    Inhomogeneous Diffusion
    Sensitivity Map
    Visual Privacy Protection
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/2824
    
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    DOI
    http://dx.doi.org/10.34944/dspace/2806
    Abstract
    We propose the use of depth-information to protect privacy in person-aware visual systems while preserving important foreground subjects and scene structures. We aim to preserve the identity of foreground subjects while hiding superfluous details in the background that may contain sensitive information. We achieve this goal by using depth information and relevant human detection mechanisms provided by the Kinect sensor. In particular, for an input color and depth image pair, we first create a sensitivity map which favors background regions (where privacy should be preserved) and low depth-gradient pixels (which often relates a lot to scene structure but little to identity). We then combine this per-pixel sensitivity map with an inhomogeneous image obscuration process for privacy protection. We tested the proposed method using data involving different scenarios including various illumination conditions, various number of subjects, different context, etc. The experiments demonstrate the quality of preserving the identity of humans and edges obtained from the depth information while obscuring privacy intrusive information in the background.
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