the design of robust face similarity features and metrics,
robust face clustering and sorting algorithms,
novel user interaction models and face recognition algorithms for face tagging,
novel applications of web face recognition,
novel computational paradigms for face recognition,
challenges in large scale face recognition tasks, e.g., on the Internet,
face recognition with contextual information,
face recognition benchmarks and evaluation methodology for moderately controlled or uncontrolled envi-ronments, and
video face recognition.
G. Hua is with the IBM T.J. Watson Research Center, Hawthorne, NY 10532. E-mail: email@example.com.
M.-H. Yang is with the Department of Electrical Engineering and Computer Science, University of California, Merced, CA 95344.
E. Learned-Miller is with the Computer Science Department, University of Massachusetts, Amherst, MA 01003. E-mail: firstname.lastname@example.org.
Y. Ma is with Microsoft Research Asia, Beijing, China, and is on leave from the Electrical and Computer Engineering Department, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
M. Turk is with the Computer Science Department, University of California, Santa Barbara, CA 93106. E-mail: email@example.com.
D.J. Kriegman is with the Computer Science and Engineering Department, University of California, San Diego, La Jolla, CA 93093.
T.S. Huang is with the Electrical and Computer Engineering Department, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
For information on obtaining reprints of this article, please send e-mail to: firstname.lastname@example.org.
Gang Hua was enrolled in the Special Class for the Gifted Young of Xian Jiaotong University (XJTU) in 1994 and received the BS degree in automatic control engineering from XJTU in 1999. He received the MS degree in control science and engineering in 2002 from XJTU, and the PhD degree from the Department of Electrical and Computer Engineering at Northwestern University in 2006. He is currently a research staff member at the IBM Research T.J. Watson Center. Before that, he was a senior researcher at Nokia Research Center, Hollywood, from 2009 to 2010, and a scientist at Microsoft Live Labs Research from 2006 to 2009. He is an associate editor of the IEEE Transactions on Image Processing and IAPR Journal of Machine Vision and Applications and a guest editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence and the International Journal on Computer Vision. He is an area chair of the IEEE International Conference on Computer Vision, 2011, an area chair of ACM Multimedia 2011, and a Workshops and Proceedings Chair of the IEEE Conference on Face and Gesture Recognition 2011. He is the author of more than 50 peer reviewed publications in prestigious international journals and conferences. As of August 2011, he holds three US patents and has 17 more patents pending. He is a senior member of the IEEE and a member of the ACM.
Ming-Hsuan Yang received the PhD degree in computer science from the University of Illinois at Urbana-Champaign in 2000. He studied at the National Tsing-Hua University, Taiwan, the University of Southern California, and the University of Texas at Austin. He is an assistant pro-fessor in electrical engineering and computer science at the University of California, Merced. He was a senior research scientist at the Honda Research Institute working on vision problems related to humanoid robots. He received the Ray Ozzie fellowship in 1999 and the Google faculty award in 2009. He coauthored the book Face Detection and Gesture Recognition for Human-Computer Interaction (Kluwer Academic, 2001) and edited a special issue on face recognition for Computer Vision and Image Understanding in 2003. He served as an area chair for the IEEE Conference on Computer Vision and Pattern Recognition, Asian Conference for the IEEE International Conference on Computer Vision, and the AAAI conference on Artificial Intelligence in 2011. He is an associate editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence and Image and Vision Computing. He is a senior member of the IEEE and the ACM.
Erik Learned-Miller (previously Erik G. Miller) is an associate professor of computer science at the University of Massachusetts, Amherst, where he joined the faculty in 2004. He spent two years as a postdoctoral researcher at the University of California, Berkeley, in the Computer Science Division. Learned-Miller received the BA degree in psychology from Yale University in 1988. In 1989, he cofounded CORITechs, Inc., where he and cofounder Rob Riker developed the second FDA cleared system for image-guided neurosurgery. He worked for Nomos Corpo-ration, Pittsburgh, Pennsylvania, for two years as the manager of neurosurgical product engineering. He received the Master of Science (1997) and PhD (2002) degrees from the Massachusetts Institute of Technology, both in electrical engineering and computer science. In 2006, he received a US National Science Foundation CAREER award for his work in computer vision and machine learning. He is a member of the IEEE.
Yi Ma received the bachelor's degree in automation and applied mathematics from Tsinghua University, Beijing, China, in 1995. He received a master's degree in electrical engineering and computer sciences (EECS) in 1997, a second master's degree in mathematics in 2000, and the PhD degree in EECS in 2000, all from the University of California, Berkeley. He is currently a professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign and, since January 2009, has also served as research manager for the Visual Computing Group at Microsoft Research Asia, Beijing, China. He received the David Marr Prize in 1999, a US National Science Foundation CAREER award in 2004, and a US Office of Naval Research Young Investigator award in 2005. He is an associate editor of the I EEE Transactions on Pattern Analysis and Machine Intelligence and the International Journal of Computer Vision. He is a senior member of the IEEE.
Matthew Turk received the BS degree from Virginia Tech, the MS degree from Carnegie Mellon University, and the PhD degree from the Massachusetts Institute of Technology. He worked for Martin Marietta Denver Aerospace from 1984 to 1987 on vision for autonomous robot navigation. In 1992, he moved to Grenoble, France, as a visiting researcher at LIFIA/ENSIMAG, then took a position at Teleos Research in 1993. In 1994, he joined Microsoft Research as a founding member of the Vision Technology Group. In 2000, he joined the faculty of the University of California, Santa Barbara, where he is now a full professor in the Computer Science Department and former chair of the Media Arts and Technology Graduate Program. He co-directs the UCSB Four Eyes Lab, where the research focus is on the “four I's” of Imaging, Interaction, and Innovative Interfaces. He is a founding member and former chair of the advisory board for the International Conference on Multimodal Interfaces and on the editorial board of the Journal of Image and Vision Computing and the ACM Transactions on Intelligent Interactive Systems. He was a general chair of the 2011 IEEE Conference on Automatic Face and Gesture Recognition. In 2011, he received the Fulbright-Nokia Distinguished Chair in Information and Communications Technologies. He is a senior member of the IEEE.
David J. Kriegman received the BSE degree in electrical engineering and computer science from Princeton University in 1983. He received the MS degree in 1984 and the PhD degree in 1989 in electrical engineering from Stanford University. Since 2002, he has been a professor of computer science and engineering in the Jacobs School of Engineering at the University of California, San Diego (UCSD). Prior to joining UCSD, he was an assistant and associate professor of electrical engineering and computer science at Yale University (1990-1998) and an associate professor with the Computer Science Department and Beckman Institute at the University of Illinois at Urbana-Champaign (1998-2002). He was founding CEO and presently serves as chief scientist of Taaz, Inc. He was chosen for a US National Science Foundation Young Investigator Award, and has received best paper awards at the 1996 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), the 1998 European Conference on Computer Vision, and the 2007 International Conference on Computer Vision (Marr Prize, runner-up), as well as the 2003 Paper of the Year Award from the Journal of Structural Biology. He served as program cochair of CVPR 2000 and general cochair of CVPR 2005. He was the editor-in-chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence from 2005-2008. He is a senior member of the IEEE.
Thomas S. Huang received the ScD degree from the Massachusetts Institute of Technology (MIT) in electrical engineering, and was on the faculty of MIT and Purdue University. He joined the University of Illinois at Urbana-Champaign in 1980 and is currently the William L. Everitt Distinguished Professor of Electrical and Computer Engineering, Research Professor of Coordinated Science Laboratory, Professor of the Center for Advanced Study, and cochair of the Human Computer Intelligent Interaction major research theme of the Beckman Institute for Advanced Science and Technology. He is a member of the National Academy of Engineering and has received numerous honors and awards, including the IEEE Jack S. Kilby Signal Processing Medal (with A. Netravali) and the King-Sun Fu Prize of the International Association of Pattern Recognition. He has published 21 books and more than 600 technical papers in network theory, digital holograpy, image and video compression, multimodal human computer interfaces, and multimedia databases. He is a fellow of the IEEE.