Share Email Print

Proceedings Paper

Dismount tracking and identification from electro-optical imagery
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

With the advent of new technology in wide-area motion imagery (WAMI) and full-motion video (FMV), there is a capability to exploit the imagery in conjunction with other information sources for improving confidence in detection, tracking, and identification (DTI) of dismounts. Image exploitation, along with other radar and intelligence information can aid decision support and situation awareness. Many advantages and limitations exist in dismount tracking analysis using WAMI/FMV; however, through layered management of sensing resources, there are future capabilities to explore that would increase dismount DTI accuracy, confidence, and timeliness. A layered sensing approach enables commandlevel strategic, operational, and tactical analysis of dismounts to combine multiple sensors and databases, to validate DTI information, as well as to enhance reporting results. In this paper, we discuss WAMI/FMV, compile a list of issues and challenges of exploiting the data for WAMI, and provide examples from recently reported results. Our aim is to provide a discussion to ensure that nominated combatants are detected, the sensed information is validated across multiple perspectives, the reported confidence values achieve positive combatant versus non- combatant detection, and the related situational awareness attributes including behavior analysis, spatial-temporal relations, and cueing are provided in a timely and reliable manner to stakeholders.

Paper Details

Date Published: 3 May 2012
PDF: 10 pages
Proc. SPIE 8402, Evolutionary and Bio-Inspired Computation: Theory and Applications VI, 84020H (3 May 2012); doi: 10.1117/12.919025
Show Author Affiliations
Erik Blasch, Air Force Research Lab. (United States)
Haibin Ling, Temple Univ. (United States)
Yi Wu, Temple Univ. (United States)
Guna Seetharaman, Air Force Research Lab. (United States)
Michael Talbert, Air Force Research Lab. (United States)
Li Bai, Temple Univ. (United States)
Genshe Chen, I-Fusion Technologies, Inc. (United States)

Published in SPIE Proceedings Vol. 8402:
Evolutionary and Bio-Inspired Computation: Theory and Applications VI
Olga Mendoza-Schrock; Mateen M. Rizki; Todd V. Rovito, Editor(s)

© SPIE. Terms of Use
Back to Top