Fusion-based approach for long-range night-time facial recognition

Robert B. Martin; Mikhail Sluch; Kristopher M. Kafka; Andrew Dolby; Robert V. Ice; Brian E. Lemoff

doi:10.1117/12.2052725

13 June 2014 Fusion-based approach for long-range night-time facial recognition

Robert B. Martin, Mikhail Sluch, Kristopher M. Kafka, Andrew Dolby, Robert V. Ice, Brian E. Lemoff

Proceedings Volume 9090, Automatic Target Recognition XXIV; 909006 (2014) https://doi.org/10.1117/12.2052725
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

Long range identification using facial recognition is being pursued as a valuable surveillance tool. The capability to perform this task covertly and in total darkness greatly enhances the operators’ ability to maintain a large distance between themselves and a possible hostile target. An active-SWIR video imaging system has been developed to produce high-quality long-range night/day facial imagery for this purpose. Most facial recognition techniques match a single input probe image against a gallery of possible match candidates. When resolution, wavelength, and uncontrolled conditions reduce the accuracy of single-image matching, multiple probe images of the same subject can be matched to the watch-list and the results fused to increase accuracy. If multiple probe images are acquired from video over a short period of time, the high correlation between the images tends to produce similar matching results, which should reduce the benefit of the fusion. In contrast, fusing matching results from multiple images acquired over a longer period of time, where the images show more variability, should produce a more accurate result. In general, image variables could include pose angle, field-of-view, lighting condition, facial expression, target to sensor distance, contrast, and image background. Long-range short wave infrared (SWIR) video was used to generate probe image datasets containing different levels of variability. Face matching results for each image in each dataset were fused, and the results compared.

Citation Download Citation

Robert B. Martin, Mikhail Sluch, Kristopher M. Kafka, Andrew Dolby, Robert V. Ice, and Brian E. Lemoff "Fusion-based approach for long-range night-time facial recognition", Proc. SPIE 9090, Automatic Target Recognition XXIV, 909006 (13 June 2014); https://doi.org/10.1117/12.2052725

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
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image fusion

Facial recognition systems

Short wave infrared radiation

Video

Video surveillance

Eye

Image quality

Show All Keywords

Keywords/Phrases

Search In:

Publication Years