• Web-scale machine-assisted annotation and retrieval of images;
• intelligent summarization and visualization for large-scale image retrieval;
• statistical and relevance feedback models for interactive search;
• annotation and retrieval for scientific discovery, biodiversity, and the arts; and
• image retrieval in computer forensics, threat assessment, and other security areas.
• J.Z. Wang is with the College of Information Sciences and Technology, The Pennsylvania State University, University Park, PA 16803.
• D. Geman is with the Department of Applied Mathematics and Statistics, Johns Hopkins University, Clark Hall 302A, 3400 N. Charles Street, Baltimore, MD 21218. E-mail: email@example.com.
• J. Luo is with Kodak Research Laboratories, Eastman Kodak Company, Rochester, NY 14650. E-mail: firstname.lastname@example.org.
• R.M. Gray is with the Department of Electrical Engineering, Stanford University, 261 Packard Building, 350 Serra Mall, Stanford, CA 94305.
For information on obtaining reprints of this article, please send e-mail to: email@example.com.
James Z. Wang received the bachelor's degree in mathematics and computer science summa cum laude from the University of Minnesota, the MS degree in mathematics and the MS degree in computer science, both from Stanford University, and the PhD degree in medical information sciences from Stanford University. He has been a faculty member in the College of Information Sciences and Technology, the Department of Computer Science and Engineering, and the Integrative Biosciences Program at The Pennsylvania State University since 2000. His main research interests are automatic image tagging, image retrieval, computational aesthetics, and computerized analysis of paintings. He was a visiting professor at the Robotics Institute at Carnegie Mellon University (2007-2008). He has also held visiting positions at SRI International, IBM Almaden Research Center, NEC Computer and Communications Research Lab, and Academia Sinica. He has been a recipient of a US National Science Foundation Career award and the endowed PNC Technologies Career Development Professorship. He is a senior member of the IEEE.
Donald Geman received the BA degree in literature from the University of Illinois and the PhD degree in mathematics from Northwestern University. He was a Distinguished Professor at the University of Massachusetts until 2001, when he joined the Department of Applied Mathematics and Statistics at The Johns Hopkins University, where he is a member of the Center for Imaging Science and the Institute for Computational Medicine. He also has an ongoing affiliation with the École Normale Supérieure de Cachan in France. He works at the intersection of applied mathematics and computer science, specializing in statistical learning, computer vision, and computational biology. Current research projects include mental image retrieval, semantic scene interpretation, molecular cancer diagnosis, and modeling protein-protein interaction networks. He is a senior member of the IEEE.
Jiebo Luo received the BS and MS degrees from the University of Science and Technology of China in 1989 and 1992, respectively, and the PhD degree from the University of Rochester in 1995, all in electrical engineering. He is a senior principal scientist with Kodak Research Laboratories, Rochester, New York. His research interests include image processing, pattern recognition, computer vision, computational photography, medical imaging, and multimedia communication. He is the author of more than 120 technical papers and holds more than 40 granted US patents. He currently serves on the editorial boards of the IEEE Transactions on Pattern Analysis and Machine Intelligence ( TPAMI), the IEEE Transactions on Multimedia ( TMM), Pattern Recognition ( PR), and the Journal of Electronic Imaging. He is a guest editor for a few special issues, including Image Understanding for Digital Photos ( PR, 2005), Real-World Image Annotation and Retrieval ( TPAMI, 2008), Event Analysis ( TCSVT, 2008), and Integration of Content and Context for Multimedia Management ( TMM, 2009). He is a Kodak Distinguished Inventor and a winner of the 2004 Eastman Innovation Award. He has also been an organizer of numerous technical conferences, including the general chair of the 2008 ACM International Conference on Image and Video Retrieval (CIVR), an area chair of the 2008 IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), a program cochair of the 2007 SPIE International Symposium on Visual Communication and Image Processing (VCIP), and a special sessions cochair of the 2006 IEEE International Conference on Multimedia and Expo (ICME). He is a senior member of the IEEE and a fellow of the SPIE.
Robert M. Gray received the BS and MS degrees from the Massachusetts Institue of Technology in 1966 and the PhD degree from the University of Southern California in 1969, all in electrical engineering. Since 1969, he has been with Stanford University, where he is currently the Alcatel Lucent Technologies Professor of Engineering and a professor of electrical engineering. His primary research interests are quantization, compression, and statistical classification. He is a fellow of the IEEE and the Institute of Mathematical Statistics and was a fellow of the John Simon Guggenheim Foundation in 1982. He was an associate editor for Source Coding (1977-1980), an editor (1980-1983) of the IEEE Transactions on Information Theory, and cochair of the 1993 IEEE International Symposium on Information Theory. He was a corecipient of the 1976 IEEE Information Theory Group Paper Award and the 1983 IEEE ASSP Senior Award. He received the IEEE Signal Processing Society 1993 Society Award, 1997 Technical Achievement Award, and 2005 Meritorious Service Award. He received IEEE Centennial and Third Millennium Medals. In 1998, he received a Golden Jubilee Award for Technological Innovation from the IEEE Information Theory Society. He received a 2002 Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring (PAESMEM). He is the recipient of the 2008 Claude E. Shannon Award of the IEEE Information Theory Society and the 2008 IEEE Jack S. Kilby Signal Processing Medal. He is a member of the National Academy of Engineering.