An automated data exploitation system for airborne sensors

Hai-Wen Chen; Mike McGurr

doi:10.1117/12.2050675

19 June 2014 An automated data exploitation system for airborne sensors

Hai-Wen Chen, Mike McGurr

Proceedings Volume 9089, Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II; 90890F (2014) https://doi.org/10.1117/12.2050675
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

Advanced wide area persistent surveillance (WAPS) sensor systems on manned or unmanned airborne vehicles are essential for wide-area urban security monitoring in order to protect our people and our warfighter from terrorist attacks. Currently, human (imagery) analysts process huge data collections from full motion video (FMV) for data exploitation and analysis (real-time and forensic), providing slow and inaccurate results. An Automated Data Exploitation System (ADES) is urgently needed. In this paper, we present a recently developed ADES for airborne vehicles under heavy urban background clutter conditions. This system includes four processes: (1) fast image registration, stabilization, and mosaicking; (2) advanced non-linear morphological moving target detection; (3) robust multiple target (vehicles, dismounts, and human) tracking (up to 100 target tracks); and (4) moving or static target/object recognition (super-resolution). Test results with real FMV data indicate that our ADES can reliably detect, track, and recognize multiple vehicles under heavy urban background clutters. Furthermore, our example shows that ADES as a baseline platform can provide capability for vehicle abnormal behavior detection to help imagery analysts quickly trace down potential threats and crimes.

Citation Download Citation

Hai-Wen Chen and Mike McGurr "An automated data exploitation system for airborne sensors", Proc. SPIE 9089, Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II, 90890F (19 June 2014); https://doi.org/10.1117/12.2050675

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