Author ORCID Identifier

http://orcid.org/0000-0002-4912-4616

Year of Publication

2016

Degree Name

Master of Science in Electrical Engineering (MSEE)

Document Type

Master's Thesis

College

Engineering

Department

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

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