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Proceedings Paper

Pattern of life from WAMI objects tracking based on visual context-aware tracking and infusion network models
Author(s): Jianjun Gao; Haibin Ling; Erik Blasch; Khanh Pham; Zhonghai Wang; Genshe Chen
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Paper Abstract

With the emergence of long lasting surveillance systems, e.g., full motion video (FMV) networks and wide area motion imagery (WAMI) sensors, extracting targets’ long term pattern of life over a day becomes possible. In this paper, we present a framework for extracting the pattern of life (POL) of targets from WAMI video. We first apply a context-aware multi-target tracker (CAMT) to track multiple targets in the WAMI video and obtain the targets’ tracklets, traces, and the locations, from surveillance information extracted from the targets' long-term trajectories. Then, entity networks propagate over time are constructed with targets’ tracklets, traces, and the interested locations. Finally, the entity network is analyzed using network retrieving technique to extract the POL of interested targets.

Paper Details

Date Published: 23 May 2013
PDF: 9 pages
Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 87451K (23 May 2013); doi: 10.1117/12.2015612
Show Author Affiliations
Jianjun Gao, Intelligent Fusion Technology, Inc. (United States)
Haibin Ling, Temple Univ. (United States)
Erik Blasch, Air Force Research Lab. (United States)
Khanh Pham, Air Force Research Lab. (United States)
Zhonghai Wang, Intelligent Fusion Technology, Inc. (United States)
Genshe Chen, Intelligent Fusion Technology, Inc. (United States)


Published in SPIE Proceedings Vol. 8745:
Signal Processing, Sensor Fusion, and Target Recognition XXII
Ivan Kadar, Editor(s)

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