Near real-time, on-the-move software PED using VPEF

Kevin Green; Chris Geyer; Chris Burnette; Sanjeev Agarwal; Bruce Swett; Chung Phan; Diane Deterline

doi:10.1117/12.2177750

14 May 2015 Near real-time, on-the-move software PED using VPEF

Kevin Green, Chris Geyer, Chris Burnette, Sanjeev Agarwal, Bruce Swett, Chung Phan, Diane Deterline

Proceedings Volume 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX; 94540O (2015) https://doi.org/10.1117/12.2177750
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

The scope of the Micro-Cloud for Operational, Vehicle-Based EO-IR Reconnaissance System (MOVERS) development effort, managed by the Night Vision and Electronic Sensors Directorate (NVESD), is to develop, integrate, and demonstrate new sensor technologies and algorithms that improve improvised device/mine detection using efficient and effective exploitation and fusion of sensor data and target cues from existing and future Route Clearance Package (RCP) sensor systems. Unfortunately, the majority of forward looking Full Motion Video (FMV) and computer vision processing, exploitation, and dissemination (PED) algorithms are often developed using proprietary, incompatible software. This makes the insertion of new algorithms difficult due to the lack of standardized processing chains. In order to overcome these limitations, EOIR developed the Government off-the-shelf (GOTS) Video Processing and Exploitation Framework (VPEF) to be able to provide standardized interfaces (e.g., input/output video formats, sensor metadata, and detected objects) for exploitation software and to rapidly integrate and test computer vision algorithms. EOIR developed a vehicle-based computing framework within the MOVERS and integrated it with VPEF. VPEF was further enhanced for automated processing, detection, and publishing of detections in near real-time, thus improving the efficiency and effectiveness of RCP sensor systems.

Citation Download Citation

Kevin Green, Chris Geyer, Chris Burnette, Sanjeev Agarwal, Bruce Swett, Chung Phan, and Diane Deterline "Near real-time, on-the-move software PED using VPEF", Proc. SPIE 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, 94540O (14 May 2015); https://doi.org/10.1117/12.2177750

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available