[4eyes] (no subject)

[Matthew Turk]

Here's a reminder of Sven Dickinson's talk on Wednesday....

 

 

UCSB COMPUTER SCIENCE DEPARTMENT PRESENTS:

 

Wednesday, October 6, 2010

11:00 AM - 12:00 PM

Computer Science Conference Room, Harold Frank Hall Rm. 1132

 

HOST: Matthew Turk

 

SPEAKER: Sven Dickinson

Department of Computer Science

University of Toronto

 

Title: The Role of Intermediate Shape Priors in Perceptual Grouping and 

Image Abstraction

 

Abstract:

 

Perceptual grouping played a prominent role in support of early object 

recognition systems, which typically took an input image and a database 

of shape models and identified which of the models was visible in the 

image.  When the database was large, local features were not 

sufficiently distinctive to prune down the space of models to a 

manageable number that could be verified.  However, when causally 

related shape features were grouped, using intermediate-level shape 

priors, e.g., cotermination, symmetry, and compactness, they formed 

effective shape indices and allowed databases to grow in size.  In 

recent years, the recognition (categorization) community has focused on 

the object detection problem, in which the input image is searched for a 

specific target object.  Since indexing is not required to select the 

target model, perceptual grouping is not required to construct a 

discriminative shape index; the existence of a much stronger 

object-level shape prior precludes the need for a weaker 

intermediate-level shape prior.  As a result, perceptual grouping 

activity at our major conferences has diminished.  However, there are 

clear signs that the recognition community is moving from appearance 

back to shape, and from detection back to unexpected object 

recognition.  Shape-based perceptual grouping will play a critical role 

in facilitating this transition.  But while causally related features 

must be grouped, they also need to be abstracted before they can be 

matched to categorical models.   In this talk, I will describe our 

recent progress on the use of intermediate shape priors in segmenting, 

grouping, and abstracting shape features.  Specifically, I will describe 

the use of symmetry and non-accidental attachment to detect and group 

symmetric parts, the use of closure to separate figure from background, 

and the use of a vocabulary of simple shape models to group and abstract 

image contours.

 

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 and Chair of the Department of 

Computer Science at the University of Toronto, where he has also served 

as Acting Chair (2008-2009), Vice Chair (2003-2006), and Associate 

Professor (2000-2007). From 1995-2000, he was an Assistant Professor of 

Computer Science at Rutgers University, where he also 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), and 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). 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.

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