Using Google Glass for photography can make you unwelcoming to people
With FaceBlock respecting personal privacy is as easy as using Google Glass itself
Being photographed without consent can be a worry
Opt out of pictures automagically with FaceBlock
If you are a Google Glass user, you might have been greeted with concerned looks or raised eyebrows at public places. FaceBlock helps to protect the privacy of people around you by allowing them to specify whether or not to be included in your pictures.
FaceBlock takes regular pictures taken by your smartphone or Google Glass as input and converts them into Privacy-Aware Pictures. These pictures are generated by using a combination of Face Detection and Face Recognition algorithms. By using FaceBlock, a user can take a picture of herself and specify her policy/rule regarding pictures taken by others (in this case ‘obscure my face in pictures from strangers’). FaceBlock would automatically generate a mathematical representation of face identifier for this picture. Using Bluetooth, FaceBlock can automatically detect and share this policy with Glass users near by.
FaceBlock is a proof of concept implementation of a system that can create Privacy-Aware Pictures using smart devices. The pervasiveness of Privacy-Aware Pictures could be a right step towards balancing privacy needs and comfort afforded by technology. Thus, we can get the best out of Wearable technology without being oblivious about the privacy of those around you. Read more here.
1. Primal Pappachan, Roberto Yus, Prajit Kumar Das, Tim Finin, Eduardo Mena and Anupam Joshi. "A Semantic Context-Aware Privacy Model for FaceBlock." In Second International Workshop on Society, Privacy and the Semantic Web-Policy and Technology (PrivOn 2014), Riva del Garda (Italy)(October 2014). 2014.
2. Roberto Yus, Primal Pappachan, Prajit Kumar Das, Eduardo Mena, Anupam Joshi and Tim Finin. "FaceBlock: Privacy-Aware Pictures for Google Glass." In Proceedings of the 12th annual international conference on Mobile systems, applications, and services, pp. 366-366. ACM, 2014.