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Proceedings Paper

Automated FMV SMART camera using dynamically updated LUTs
Author(s): Holger Jaenisch; James Handley
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Paper Abstract

We present a method for segmenting FMV video streams to dynamically extract scene recognition and change detection information using simple on-the-fly statistics. We show how the video scene can be segmented enabling sub-frame statistical characterization. The features are written into dynamic look-up tables (LUTs) in real-time. Behavior recognition occurs by testing if the newly observed scene statistics have already been recorded in the table. The features in the LUT can later be used to derive predictive behavior Data Models. We demonstrate results of our approach on various types of FMV and micro UAV video data streams.

Paper Details

Date Published: 25 May 2012
PDF: 13 pages
Proc. SPIE 8386, Full Motion Video (FMV) Workflows and Technologies for Intelligence, Surveillance, and Reconnaissance (ISR) and Situational Awareness, 83860H (25 May 2012); doi: 10.1117/12.914735
Show Author Affiliations
Holger Jaenisch, The Johns Hopkins Univ. (United States)
Licht Strahl Engineering Inc. (United States)
James Handley, Licht Strahl Engineering Inc. (United States)


Published in SPIE Proceedings Vol. 8386:
Full Motion Video (FMV) Workflows and Technologies for Intelligence, Surveillance, and Reconnaissance (ISR) and Situational Awareness
Donnie Self, Editor(s)

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