13 May 2016 Real-time WAMI streaming target tracking in fog
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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.
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Yu Chen, Erik Blasch, Ning Chen, Anna Deng, Haibin Ling, Genshe Chen, "Real-time WAMI streaming target tracking in fog", Proc. SPIE 9838, Sensors and Systems for Space Applications IX, 98380D (13 May 2016); doi: 10.1117/12.2223975; https://doi.org/10.1117/12.2223975
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