Computing That Serves

The Role of Symmetry in Computer and Human Vision


Thursday, April 13, 2017 - 11:00am


Sven Dickinson


Ryan Farrell

Symmetry is one of the most ubiquitous regularities in our natural world.  For almost 100 years, human vision researchers have studied how the human vision system has evolved to exploit this powerful regularity as a basis for grouping image features and, for almost 50 years, as a basis for how the human vision system might encode the shape of an object.  While computer vision is a much younger discipline, the trajectory is similar, with symmetry playing a major role in both perceptual grouping and object representation.  After briefly reviewing some of the milestones in symmetry-based perceptual grouping and object representation/recognition in both human and computer vision, I will articulate some of the research challenges.  I will then briefly describe some of our recent efforts to address these challenges, including the detection and grouping of locally symmetric parts in complex imagery and understanding the role of symmetry in human scene perception.


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 will become 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.