CMU-CS-12-147
Computer Science Department
School of Computer Science, Carnegie Mellon University


CMU-CS-12-147

Scalable Crowd-Sourcing of Video from Mobile Devices

Pieter Simoens*, Yu Xiao**, Padmanabhan Pillai***, Zhuo Chen,
Kiryong Ha, Mahadev Satyanarayanan

December 2012

CMU-CS-12-147.pdf


Keywords: Mobile computing, cloud computing, Google Glass, headup display, HUD, first-person vision system, FPV, sensing, smartphones, virtual machines, system architecture, cloudlets, denaturing, face detection, face recognition, content-based search, image search, early discard, Diamond

We propose a scalable Internet system for continuous collection of crowd-sourced video from devices such as Google Glass. Our hybrid cloud architecture for this system is effectively a CDN in reverse. It achieves scalability by decentralizing the cloud computing infrastructure using VM-based cloudlets. Based on time, location and content, privacy sensitive information is automatically removed from the video. This process, which we refer to as denaturing, is executed in a user-specific Virtual Machine (VM) on the cloudlet. Users can perform content-based searches on the total catalog of denatured videos. Our experiments reveal the bottlenecks for video upload, denaturing, indexing and content-based search and provide valuable insight on how parameters such as frame rate and resolution impact the system scalability.

21 pages

*Carnegie Mellon University and Ghent University
**Carnegie Mellon University and Aalto University
***Intel Labs

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