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Proceedings Paper

Real-time WAMI streaming target tracking in fog
Author(s): Yu Chen; Erik Blasch; Ning Chen; Anna Deng; Haibin Ling; Genshe Chen
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Paper Abstract

Real-time information fusion based on WAMI (Wide-Area Motion Imagery), FMV (Full Motion Video), and Text data is highly desired for many mission critical emergency or security applications. Cloud Computing has been considered promising to achieve big data integration from multi-modal sources. In many mission critical tasks, however, powerful Cloud technology cannot satisfy the tight latency tolerance as the servers are allocated far from the sensing platform, actually there is no guaranteed connection in the emergency situations. Therefore, data processing, information fusion, and decision making are required to be executed on-site (i.e., near the data collection). Fog Computing, a recently proposed extension and complement for Cloud Computing, enables computing on-site without outsourcing jobs to a remote Cloud. In this work, we have investigated the feasibility of processing streaming WAMI in the Fog for real-time, online, uninterrupted target tracking. Using a single target tracking algorithm, we studied the performance of a Fog Computing prototype. The experimental results are very encouraging that validated the effectiveness of our Fog approach to achieve real-time frame rates.

Paper Details

Date Published: 13 May 2016
PDF: 11 pages
Proc. SPIE 9838, Sensors and Systems for Space Applications IX, 98380D (13 May 2016); doi: 10.1117/12.2223975
Show Author Affiliations
Yu Chen, Binghamton Univ. (United States)
Erik Blasch, Air Force Research Lab. (United States)
Ning Chen, Binghamton Univ. (United States)
Anna Deng, Binghamton Univ. (United States)
Haibin Ling, Temple Univ. (United States)
Genshe Chen, Intelligent Fusion Technology, Inc. (United States)

Published in SPIE Proceedings Vol. 9838:
Sensors and Systems for Space Applications IX
Khanh D. Pham; Genshe Chen, Editor(s)

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