Author ORCID Identifier
Date Available
12-9-2016
Year of Publication
2016
Degree Name
Master of Science in Electrical Engineering (MSEE)
Document Type
Master's Thesis
College
Engineering
Department/School/Program
Electrical and Computer Engineering
First Advisor
Dr. Sen-Ching S. Cheung
Abstract
Wearable cameras are increasingly used in many different applications such as entertainment, security, law enforcement and healthcare. In this thesis, we focus on the application of the police worn body camera and behavioral recording using a wearable camera for one-on-one therapy with a child in a classroom or clinic. To protect the privacy of other individuals in the same environment, we introduce a new visual privacy protection technique called visual bubble. Visual bubble is a virtual zone centered around the camera for observation whereas the rest of the environment and people are obfuscated. In contrast to most existing visual privacy protection systems that rely on visual classifiers, visual bubble is based on depth estimation to determine the extent of privacy protection. To demonstrate this concept, we construct a wearable stereo camera for depth estimation on the Raspberry Pi platform. We also propose a novel framework to quantify the uncertainty in depth measurements so as to minimize a statistical privacy risk in constructing the depth-based privacy bubble. To evaluate our system, we have collected three datasets. The effectiveness of the proposed scheme is demonstrated with experimental results.
Digital Object Identifier (DOI)
https://doi.org/10.13023/ETD.2016.514
Recommended Citation
Wang, Shaoqian, "WEARABLE PRIVACY PROTECTION WITH VISUAL BUBBLE" (2016). Theses and Dissertations--Electrical and Computer Engineering. 97.
https://uknowledge.uky.edu/ece_etds/97
