FaceKeeper - Privacy-Aware Distributed Computation of Family Photo Collections

Abstract

Family photos are personal, private information. There is a need for alternative storage models for secure, private (offline) media archiving & curation. Server-Client relations are now changing from centralized form of network to distributed and decentralized network. The centralized network model provides all of the privacy control of users to the host of the network. The research objective of the project was to design a novel system for family photo collection analysis by leveraging local home networking, reducing dependence on cloud services prioritizing privacy and maximizing sustainability through device reuse (IOT). The outcomes and deliverables of the research included: A robust face clustering algorithm written in Python, with documentation available for open source use on GitHub. Reverse Image Search on Photo Collection feature was built complementing the research. The delivered software supports device re-use by supporting single-board computers such as Raspberry Pi.