Unsupported Browser

Your Browser is out of date and is not supported by this website.
Please upgrade to Firefox, Chrome, or Microsoft Edge.

The Founding College of the University of Toronto
Search this site
Midshot of Sven Dickinson

Sven Dickinson

Faculty
Professor, Department of Computer Science
416-978-3853
416-978-1455
Website
283B Pratt Building
6 King's College Rd., Toronto, ON M5S 3G4

 

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 Professor and past Chair of the Department of Computer Science at the University of Toronto, and is also Vice President and Head of the new Samsung Toronto AI Research Center, which opened in May, 2018. Prior to that, he was a faculty member at Rutgers University where he held a joint appointment between the Department of Computer Science and the Rutgers Center for Cognitive Science (RuCCS). His research interests revolve around the problem of shape perception in computer vision and, more recently, human vision. He has received the National Science Foundation CAREER award, the Government of Ontario Premiere's Research Excellence Award (PREA), and the Lifetime Research Achievement Award from the Canadian Image Processing and Pattern Recognition Society (CIPPRS). He was the Editor-in-Chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence, from 2017-2021, currently serves on seven editorial boards, and is co-editor of the Morgan & Claypool Synthesis Lectures on Computer Vision. He is a Fellow of the International Association for Pattern Recognition (IAPR), and an IEEE Golden Core Member.

  • BASc (Systems Design Engineering), University of Waterloo
  • MSc (Computer Science), University of Maryland at College Park.
  • PhD (Computer Science), University of Maryland at College

Shape perception in computer vision and human vision; perceptual grouping and its role in image segmentation and shape recovery; qualitative shape representations and their basis in symmetry; object recognition; multiscale, parts-based shape representations and their common abstraction as hierarchical graphs; inexact graph indexing and matching; object tracking, vision-based navigation, content-based image retrieval, language-vision integration, and image/model abstraction.