Abstract
This chapter presents a study of face recognition performance as a function of light level using intensified near infrared imagery in conjunction with thermal infrared imagery. Intensification technology is the most prevalent in both civilian and military night vision equipment and provides enough enhancement for human operators to perform standard tasks under extremely low light conditions. We describe a comprehensive data collection effort undertaken to image subjects under carefully controlled illumination and quantify the performance of standard face recognition algorithms on visible, intensified, and thermal imagery as a function of light level. Performance comparisons for automatic face recognition are reported using the standardized implementations from the Colorado State University Face Identification Evaluation System, as well as Equinox's algorithms. The results contained in this chapter should constitute the initial step for analysis and deployment of face recognition systems designed to work in low-light conditions.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Chapter's References
D.A. Socolinsky and A. Selinger, A comparative analysis of face recognition performance with visible and thermal infrared imagery, in Proceedings ICPR, Quebec, Canada, August 2002.
D.A. Socolinsky and A. Selinger, Face recognition with visible and thermal infrared imagery, Computer Vision and Image Understanding, July–August 2003
J. Wilder, P.J. Phillips, C. Jiang, and S. Wiener, Comparison of Visible and Infra-Red Imagery for Face Recognition, in Proceedings of 2nd International Conference on Automatic Face & Gesture Recognition, Killington, VT, 1996, pp. 182–187
X. Chen, P. Flynn, and K. Bowyer, Visible-light and infrared face recognition, in Proceedings of the Workshop on Multimodal User Authentication, Santa Barbara, CA, December 2003
B. Abidi, Performance comparison of visual and thermal signatures for face recognition, in The Biometrics Consortium Conference, Arlington, VA, September 2003
F.J. Prokoski, History, current status, and future of infrared identification, in Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, Hilton Head, NC, 2000
D. Bolme, R. Beveridge, M. Teixeira, and B. Draper, The CSU face identification evaluation system: its purpose, features and structure, in Proceedings of the International Conference on Vision Systems, Graz, Austria, April 2003, pp. 304–311, Springer-Verlag, New York.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Socolinsky, D.A., Wolff, L.B. (2009). Face Recognition in Low-Light Environments Using Fusion of Thermal Infrared and Intensified Imagery. In: Hammoud, R.I. (eds) Augmented Vision Perception in Infrared. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84800-277-7_9
Download citation
DOI: https://doi.org/10.1007/978-1-84800-277-7_9
Publisher Name: Springer, London
Print ISBN: 978-1-84800-276-0
Online ISBN: 978-1-84800-277-7
eBook Packages: Computer ScienceComputer Science (R0)