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Proceedings Paper

Activity-based intelligence tipping and cueing using polarimetric sensors
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Paper Abstract

Activity Based Intelligence (ABI) is the derivation of information from the composite of a series of individual actions being recorded over a period of time. Due to its temporal nature, ABI is usually developed from Motion Imagery (MI) or Full Motion Video (FMV) taken of a given scene. One of today's common issues is sifting through such large volumes of temporal data. Here we propose using a technique known as tipping an cueing to alleviate the need to manually sift through said data. Being able to tip the analysts or automated algorithm towards a particular person or object in the data is useful in reducing search time. We propose using a polarimetric sensor to identify objects of interest, in a scene where their signature would be unusual. Once identified, this data will be used to cue a FMV RGB sensor to track the object and determine the activities being executed by the person bringing the object into the scene.

Paper Details

Date Published: 21 May 2014
PDF: 13 pages
Proc. SPIE 9099, Polarization: Measurement, Analysis, and Remote Sensing XI, 90990C (21 May 2014); doi: 10.1117/12.2050743
Show Author Affiliations
Christian M. Lewis, Rochester Institute of Technology (United States)
Air Force Institute of Technology (United States)
David Messinger, Rochester Institute of Technology (United States)
Michael G. Gartley, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 9099:
Polarization: Measurement, Analysis, and Remote Sensing XI
David B. Chenault; Dennis H. Goldstein, Editor(s)

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