Simulating human vehicle identification performance with infrared imagery and augmented reality assistance

John J. Graybeal; Rachel T. T. Nguyen; Todd W. Du Bosq

doi:10.1117/12.2518990

14 May 2019 Simulating human vehicle identification performance with infrared imagery and augmented reality assistance

John J. Graybeal, Rachel T. T. Nguyen, Todd W. Du Bosq

Proceedings Volume 11001, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX; 110010A (2019) https://doi.org/10.1117/12.2518990
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

The U.S. Army CCDC C5ISR Night Vision and Electronic Sensors Directorate is researching the use of augmented reality (AR) technologies to improve the situational awareness and decision-making capabilities of EO/IR sensor operators. A major research requirement for such technologies involves defining the accuracy of AR information required to improve human performance for tasks related to EO/IR sensors, as AR systems may unintentionally provide inaccurate information to operators, which may be worse than providing no information at all. We designed a simulation to assess human performance during a vehicle identification task (using infrared imagery) when the operator receives aid via an AR system. U.S. Soldiers, trained to identify vehicles using infrared sensors, viewed images of the vehicles at different ranges in blocks while a simulated AR system attempted to identify each vehicle. Each block of images possessed an inherent level of AR accuracy (either 100%, 75%, or 50%). Performance with AR was compared to baseline performance (i.e., completing the task with no AR assistance). We further explored human performance by examining time-constrained decisions with AR. While perfect AR information was generally used effectively by participants, AR mistakes progressively increased human errors and slowed response times. Human performance varied as the range to the target increased, indicating greater dependency on the AR system as the task became more difficult. Time constraints reduced identification accuracy and usually affected unaided and aided performance similarly. Our work demonstrates the importance of simulation as a tool for understanding the effects of AR on military task performance.

Citation Download Citation

John J. Graybeal, Rachel T. T. Nguyen, and Todd W. Du Bosq "Simulating human vehicle identification performance with infrared imagery and augmented reality assistance", Proc. SPIE 11001, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXX, 110010A (14 May 2019); https://doi.org/10.1117/12.2518990

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
14 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Augmented reality

Sensors

Reliability

Performance modeling

Infrared imaging

Data modeling

Long wavelength infrared

Show All Keywords

Keywords/Phrases

Search In:

Publication Years