Heterogeneous Face Recognition

GRAND Seminar Feb. 12, 12 PM., Tue. 2013, ENGR 4201

Brendan Klare
Lead Scientist at Noblis

Slides: pdf

Abstract:

A chief benefit of face recognition technology is the extensive collection of face photographs available to populate target galleries. From sources such as driver's licenses, passports, and mug shots, a (generally) high quality gallery seed exists for a large percentage of the developed world's population. While these gallery images are visible light photographs, many face recognition scenarios exist where probe images used to be match against such galleries are only available from some alternate imaging modality. For example, in environments with adverse illumination conditions (such as nighttime), face images must be captured in the infrared spectrum. In other cases, a lack of a face image requires the use of a forensic sketch to depict a subject. The task of matching face images across image modalities is called heterogeneous face recognition. In this talk, the problem of heterogeneous face recognition will be introduced. Different approaches for performing heterogeneous face recognition will be introduced, including methods for (i) directly measuring the similarity between heterogeneous face images, and (ii) using prototype similarities to performing matching without needing a direct comparison. The follow research topics will also be discussed: (i) the effect of demographics (race, gender, and age) on face recognition performance, (ii) studies on training face recognition system for time lapse invariance, and (iii) designing facial features and matching algorithms for matching caricature sketches to photographs.

Short Bio:

Brendan Klare is a scientist at Noblis. He received the Ph.D. degree in Computer Science from Michigan State University in 2012, and received the B.S. and M.S. degrees in Computer Science and Engineering from the University of South Florida in 2007 and 2008. From 2001 to 2005 he served as an airborne ranger infantryman in the 75th Ranger Regiment, U.S. Army. Brendan has authored several papers on the topic of face recognition, and was the recipient of the Honeywell Best Student Paper Award at the 2010 IEEE Conference on Biometrics: Theory, Applications and Systems (BTAS). His other research interests include pattern recognition and computer vision.

Related Publications:

B. F. Klare, Z. Li, and A.K. Jain, "Matching Forensic Sketches to Mug Shot Photos," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, no.3, pp.639-646, 2011.

B. F. Klare and A.K. Jain, "Heterogeneous Face Recognition using Kernel Prototype Similarities," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012 (to appear).

B. F. Klare, M. Burge, J. Klontz, R.W. Vorder Bruegge, and A. K. Jain, "Face Recognition Performance: Role of Demographic Information", IEEE Transactions on Information Forensics and Security, 2012 (To Appear).

B. F. Klare and A. K. Jain, "Face Recognition Across Time Lapse: On Learning Feature Subspaces", Proceedings of the International Joint Conference on Biometrics, 2011.