Dismount tracking and identification from electro-optical imagery

Erik Blasch; Haibin Ling; Yi Wu; Guna Seetharaman; Michael Talbert; Li Bai; Genshe Chen

doi:10.1117/12.919025

3 May 2012 Dismount tracking and identification from electro-optical imagery

Erik Blasch, Haibin Ling, Yi Wu, Guna Seetharaman, Michael Talbert, Li Bai, Genshe Chen

Proceedings Volume 8402, Evolutionary and Bio-Inspired Computation: Theory and Applications VI; 84020H (2012) https://doi.org/10.1117/12.919025
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Erik Blasch, Haibin Ling, Yi Wu, Guna Seetharaman, Michael Talbert, Li Bai, and Genshe Chen "Dismount tracking and identification from electro-optical imagery", Proc. SPIE 8402, Evolutionary and Bio-Inspired Computation: Theory and Applications VI, 84020H (3 May 2012); https://doi.org/10.1117/12.919025

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