Democratizing Facial Recognition with Google Glass
Abstract
Lightweight and camera-equipped wearable devices such as Android-backed
Google Glass— with their potential for wide-spread and mobile data
capture—have piqued the imagination of technologists and privacy
advocates alike. This paper describes an experimental system which
confirms the feasibility of such devices for surveillance through live
data collection and facial recognition. Furthermore, even though
effective surveillance tasks are computationally demanding, this work
illustrates that performance of such systems is scalable through careful
architecting of communication between static servers and mobile
collection devices. When the bulk of the complexity can be offloaded to
the server, and with the availability of highly-available communication
channels between collector and processor, we have the foundation upon
which future surveillance systems might be constructed. Such systems
awaken nightmares for those advocating privacy of the modern citizen,
while inspiring innovators to push forward the bounds of what can be
accomplished with today’s technology. The present project enables
advocates from both ends of the spectrum to debate privacy policy as it
can be seen through the lens of systems that are possible today.