Glance Privacy: Obfuscating Personal Identity While Coding Behavioral Video

Authors

  • Mitchell Gordon University of Rochester
  • Walter Lasecki Carnegie Mellon University
  • Winnie Leung Carnegie Mellon University
  • Ellen Lim Carnegie Mellon University
  • Steven Dow Carnegie Mellon University
  • Jeffery Bigham Carnegie Mellon University

DOI:

https://doi.org/10.1609/hcomp.v2i1.13173

Abstract

Behavioral researchers code video to extract systematic meaning from subtle human actions and emotions. While this has traditionally been done by analysts within a research group, recent methods have leveraged online crowds to massively parallelize this task and reduce the time required from days to seconds. However, using the crowd to code video increases the risk that private information will be disclosed because workers who have not been vetted will view the video data in order to code it. In this Work-in-Progress, we discuss techniques for maintaining privacy when using Glance to code video and present initial experimental evidence to support them.

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Published

2014-09-05

How to Cite

Gordon, M., Lasecki, W., Leung, W., Lim, E., Dow, S., & Bigham, J. (2014). Glance Privacy: Obfuscating Personal Identity While Coding Behavioral Video. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2(1), 18-19. https://doi.org/10.1609/hcomp.v2i1.13173

Issue

Vol. 2 (2014): Second AAAI Conference on Human Computation and Crowdsourcing

Section

Works in Progress