Keynote Speakers




  • Prof. Rama Chellappa
    University of Maryland
    BIO
    Prof. Rama Chellappa received the B.E. (Hons.) degree from the University of Madras, Madras, India, in 1975, the M.E. (Distinction) degree from the Indian Institute of Science, Bangalore, India, in 1977, and the M.S.E.E. and Ph.D. degrees in electrical engineering from Purdue University, West Lafayette, IN, in 1978 and 1981, respectively. Since 1991, he has been a Professor of Electrical Engineering and an affiliate Professor of Computer Science with the University of Maryland, College Park. He is also affiliated with the Center for Automation Research (Director) and the Institute for Advanced Computer Studies (Permanent Member). In 2005, he was named a Minta Martin Professor of Engineering. Prior to joining the University of Maryland, he was an Assistant (1981–1986) and Associate Professor (1986–1991) and Director of the Signal and Image Processing Institute (1988–1990) with the University of Southern California, Los Angeles. Over the last 30 years, he has published numerous book chapters, peer-reviewed journal and conference papers. He has coauthored and coedited books on MRFs, face and gait recognition and collected works on image processing and analysis. He has served as a Co-Editor-in-Chief of Graphical Models and Image Processing. His current research interests are face and gait analysis, markerless motion capture, 3-D modeling from video, image and video-based recognition and exploitation, compressive sensing, and hyper spectral processing.
    Prof. Chellappa has received several awards, including a National Science Foundation Presidential Young Investigator Award, four IBM Faculty Development Awards, an Excellence in Teaching Award from the School of Engineering at USC, and two paper awards from the International Association of Pattern Recognition. He received the Society, Technical Achievement and Meritorious Service Awards from the IEEE Signal Processing Society. He also received the Technical Achievement and Meritorious Service Awards from the IEEE Computer Society. At the University of Maryland, he was elected as a Distinguished Faculty Research Fellow, as a Distinguished Scholar-Teacher, received the Outstanding Faculty Research Award and the Poole and Kent Teaching Award for the Senior Faculty from the College of Engineering, an Outstanding Innovator Award from the Office of Technology Commercialization and an Outstanding GEMSTONE Mentor Award. In 2010, he was recognized as an Outstanding ECE by Purdue University. He is a Fellow of the IEEE, the International Association for Pattern Recognition and the Optical Society of America. He has served as an associate editor for four IEEE publications and as the Editor-in-Chief of the IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE. He served as a member of the IEEE Signal Processing Society Board of Governors and as its Vice President of Awards and Membership. He has served as a General and Technical Program Chair for several IEEE international and national conferences and workshops. He is a Golden Core Member of the IEEE Computer Society and served a two-year term as a Distinguished Lecturer of the IEEE Signal Processing Society. Recently, he completed a two-year term as the President of IEEE Biometrics Council.



  • Prof. Sven Dickinson
    University of Toronto
    The Role of Symmetry in Human and Computer Vision
    BIO
    Sven Dickinson received the B.A.Sc. degree in Systems Design Engineering from the University of Waterloo, in 1983, and the M.S. and Ph.D. degrees in Computer Science from the University of Maryland, in 1988 and 1991, respectively. He is currently Professor of the Department of Computer Science at the University of Toronto, where he has served as Chair (2010-2015), Acting Chair (2008-2009), and Vice Chair (2003-2006). From 1995-2000, he was Assistant Professor of Computer Science at Rutgers University, where he held a joint appointment in the Rutgers Center for Cognitive Science (RuCCS) and membership in the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS). From 1994-1995, he was a Research Assistant Professor in the Rutgers Center for Cognitive Science, and from 1991-1994, a Research Associate at the Artificial Intelligence Laboratory, University of Toronto. He has held affiliations with the MIT Media Laboratory (Visiting Scientist, 1992-1994), the University of Toronto (Visiting Assistant Professor, 1994-1997), the Computer Vision Laboratory of the Center for Automation Research at the University of Maryland (Assistant Research Scientist, 1993-1994, Visiting Assistant Professor, 1994-1997), and the University of California, Santa Barbara (Visiting Professor, 2010-2011, 2015-2016). Prior to his academic career, he worked in the computer vision industry, designing image processing systems for Grinnell Systems Inc., San Jose, CA, 1983-1984, and optical character recognition systems for DEST, Inc., Milpitas, CA, 1984-1985.
    Dr. Dickinson's research interests revolve around the problem of shape perception in computer vision and, more recently, human vision. Much of his recent work focuses on perceptual grouping and its role in image segmentation and shape recovery. He's introduced numerous qualitative shape representations, and their basis in symmetry provides a focus for his perceptual grouping research. His interest in multiscale, parts-based shape representations, and their common abstraction as hierarchical graphs, has motivated his research in inexact graph indexing and matching -- key problems in object recognition, another broad focus of his research. His research has also explored many problems related to object recognition, including object tracking, vision-based navigation, content-based image retrieval, language-vision integration, and image/model abstraction.
    In 1996, Dr. Dickinson received the NSF CAREER award for his work in generic object recognition, and in 2002, received the Government of Ontario Premiere's Research Excellence Award (PREA), also for his work in generic object recognition. In 2012, he received the Lifetime Research Achievement Award from the Canadian Image Processing and Pattern Recognition Society (CIPPRS). In an effort to bring together researchers from human and computer vision, he was co-chair of the 1997, 1999, 2004, and 2007 IEEE International Workshops on Generic Object Recognition (or Object Categorization), which culminated in the interdisciplinary volume, Object Categorization: Computer and Human Vision Perspectives, in 2009, and was co-chair of the 2008, 2009, 2010, and 2011 International Workshops on Shape Perception in Human and Computer Vision, which culminated in the interdisciplinary volume, Shape Perception in Human and Computer Vision: An Interdisciplinary Perspective, in 2013. He was General Co-Chair of the 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), and currently serves or has served on the editorial boards of the journals: IEEE Transactions on Pattern Analysis and Machine Intelligence; International Journal of Computer Vision; Computer Vision and Image Understanding; Image and Vision Computing; Graphical Models; Pattern Recognition Letters; IET Computer Vision; and the Journal of Electronic Imaging. In 2017, he became Editor-in-Chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence. He is also co-editor of the Synthesis Lectures on Computer Vision from Morgan & Claypool Publishers, since its inauguration in 2009.



  • Prof. Shaogang (Sean) Gong
    Queen Mary University of London
    People Search In Large Scale Videos
    BIO
    Gong is Professor of Visual Computation at Queen Mary University of London, elected a Fellow of the Institution of Electrical Engineers, a Fellow of the British Computer Society, a member of the UK Computing Research Committee, and served on the Steering Panel of the UK Government Chief Scientific Advisor's Science Review.
    Prof. Gong's early interest was in information theory & measurement and received a B.Sc. from the University of Electronic Sciences and Technology of China in 1985. Gong's B.Sc. thesis project was on biomedical image analysis which gave him the opportunity to develop a wider interest in robotics. This led Gong to pursue a doctorate in computer vision under the supervision of Mike Brady at Keble College Oxford and the Oxford Robotics Group in 1986. Brady introduced Gong to differential geometry in computer vision and the work of Ellen Hildreth at the MIT AI Lab on computing optic flow. During that time, Gong met David Murray who was on sabbatical at Oxford from GEC Hirst. Murray introduced Gong to the extensive work by Murray and Bernard Buxton at the GEC Hirst Centre on structure-from-motion for autonomous guided vehicle navigation. Gong received his D.Phil. from Oxford in 1989 with a thesis on computing optic flow by second-order geometrical analysis of Hessian derivatives with wave-diffusion propagation. Gong is a recipient of a Queen's Research Scientist Award in 1987, a Royal Society Research Fellow in 1987 and 1988, and a GEC sponsored Oxford research fellow in 1989.
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