Visual Bubble: Protecting Privacy in Wearable Cameras

Shaoqian Wang, Sen Ching S. Cheung, Hasan Sajid

Research output: Contribution to specialist publicationArticle

2 Scopus citations

Abstract

Wearable cameras are being used more frequently in many different consumer applications, including entertainment, law enforcement, and health care. To protect the privacy of the environment and bystanders, we introduce a new visual privacy paradigm called the visual bubble. In contrast to most existing visual privacy schemes, the visual bubble is based on depth estimation to determine the extent of privacy protection. To demonstrate this concept, we built a wearable privacy stereo-camera system using the Raspberry Pi platform. The effectiveness of our system in protecting privacy was demonstrated with experimental results on multiple data sets.

Original languageEnglish
Pages95-105
Number of pages11
Volume7
No1
Specialist publicationIEEE Consumer Electronics Magazine
DOIs
StatePublished - Jan 2018

Bibliographical note

Funding Information:
Part of this material is based on work supported by the National Science Foundation under Grant 1237134. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Funding Information:
Part of this material is based on work supported by the National Science Foundation under Grant 1237134.

Publisher Copyright:
© 2012 IEEE.

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Science Applications
  • Electrical and Electronic Engineering

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