Color constancy in 3D-2D face recognition

Manuel Meyer; Christian Riess; Elli Angelopoulou; Georgios Evangelopoulos; Ioannis A. Kakadiaris

doi:10.1117/12.2018758

31 May 2013 Color constancy in 3D-2D face recognition

Manuel Meyer, Christian Riess, Elli Angelopoulou, Georgios Evangelopoulos, Ioannis A. Kakadiaris

Proceedings Volume 8712, Biometric and Surveillance Technology for Human and Activity Identification X; 87120S (2013) https://doi.org/10.1117/12.2018758
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Face is one of the most popular biometric modalities. However, up to now, color is rarely actively used in face recognition. Yet, it is well-known that when a person recognizes a face, color cues can become as important as shape, especially when combined with the ability of people to identify the color of objects independent of illuminant color variations. In this paper, we examine the feasibility and effect of explicitly embedding illuminant color information in face recognition systems. We empirically examine the theoretical maximum gain of including known illuminant color to a 3D-2D face recognition system. We also investigate the impact of using computational color constancy methods for estimating the illuminant color, which is then incorporated into the face recognition framework. Our experiments show that under close-to-ideal illumination estimates, one can improve face recognition rates by 16%. When the illuminant color is algorithmically estimated, the improvement is approximately 5%. These results suggest that color constancy has a positive impact on face recognition, but the accuracy of the illuminant color estimate has a considerable effect on its benefits.

Citation Download Citation

Manuel Meyer, Christian Riess, Elli Angelopoulou, Georgios Evangelopoulos, and Ioannis A. Kakadiaris "Color constancy in 3D-2D face recognition", Proc. SPIE 8712, Biometric and Surveillance Technology for Human and Activity Identification X, 87120S (31 May 2013); https://doi.org/10.1117/12.2018758

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

Facial recognition systems

Skin

Databases

Cameras

3D modeling

Biometrics

Volume rendering

Show All Keywords

Keywords/Phrases

Search In:

Publication Years