Overview of the Multiple Biometrics Grand Challenge

Authors:
P. Jonathon Phillips;Patrick J. Flynn;J. Ross Beveridge;W. Todd Scruggs;Alice J. O'Toole;David Bolme;Kevin W. Bowyer;Bruce A. Draper;Geof H. Givens;Yui Man Lui;Hassan Sahibzada;Joseph A. Scallan, Iii;Samuel Weimer
Affiliations:
National Institute of Standards and Technology, Gaithersburg, USA MD 20899;Computer Science & Engineering Department, U. of Notre Dame, Notre Dame, USA IN 46556;Department of Computer Science, Colorado State U., Fort Collins, USA CO 80523;SAIC, Arlington, USA VA 22203;School of Behavioral and Brain Sciences, The U. of Texas at Dallas, Richardson, USA TX 75083;Department of Computer Science, Colorado State U., Fort Collins, USA CO 80523;Computer Science & Engineering Department, U. of Notre Dame, Notre Dame, USA IN 46556;Department of Computer Science, Colorado State U., Fort Collins, USA CO 80523;Department of Statistics, Colorado State U., Fort Collins, USA CO 80523;Department of Computer Science, Colorado State U., Fort Collins, USA CO 80523;National Institute of Standards and Technology, Gaithersburg, USA MD 20899;Schafer Corp., Arlington, USA VA 22203;School of Behavioral and Brain Sciences, The U. of Texas at Dallas, Richardson, USA TX 75083
Venue:
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Year:
2009

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Abstract

The goal of the Multiple Biometrics Grand Challenge (MBGC) is to improve the performance of face and iris recognition technology from biometric samples acquired under unconstrained conditions. The MBGC is organized into three challenge problems. Each challenge problem relaxes the acquisition constraints in different directions. In the Portal Challenge Problem, the goal is to recognize people from near-infrared (NIR) and high definition (HD) video as they walk through a portal. Iris recognition can be performed from the NIR video and face recognition from the HD video. The availability of NIR and HD modalities allows for the development of fusion algorithms. The Still Face Challenge Problem has two primary goals. The first is to improve recognition performance from frontal and off angle still face images taken under uncontrolled indoor and outdoor lighting. The second is to improve recognition performance on still frontal face images that have been resized and compressed, as is required for electronic passports. In the Video Challenge Problem, the goal is to recognize people from video in unconstrained environments. The video is unconstrained in pose, illumination, and camera angle. All three challenge problems include a large data set, experiment descriptions, ground truth, and scoring code.