[Colloquium] Research at TTIC: Devi Parikh

[Liv Leader]

REMINDER:

When:     Friday, February 10th @ 3 p.m.

Where:    TTIC, 6045 S. Kenwood Avenue, 4th Floor Common Area

Who:       Devi Parikh

Title:       Advancing Computer Vision via Human-Machine Collaboration

Computer vision has made a lot of progress in the past several decades.
However, aside from our roles as researchers and perhaps ground-truth
generating minions, humans play a limited role in advancing the state of
the art. This seems rather counter-productive since humans are often a
working system whose performance we aim for machines to replicate (e.g. in
semantic image understanding), and are frequently users of the technology
(e.g. in image search). In this talk, I will describe my recent efforts in
involving humans in advancing computer vision.

In the first part of my talk, I will describe our recently-introduced
"human-debugging" paradigm. It allows us to identify the aspects of machine
vision approaches that require future research efforts. It involves
replacing various components of a machine vision pipeline with human
subjects, and examining the resultant effect on recognition performance. I
will present several of our efforts within this framework that address
image classification, object recognition and person detection. I will
discuss the lessons learnt and present subsequent improvements to computer
vision algorithms inspired by these findings.

In the second part of my talk, I will present our work on allowing humans
and machines to better communicate with each other. We utilize visual
attributes as a mode of communication. Visual attributes are mid-level
concepts such as "furry" and "metallic" that bridge the gap between
low-level image features (e.g. texture) and high-level concepts (e.g.
rabbit or car). They are shareable across different but related concepts.
Most importantly, visual attributes are both machine detectable and human
understandable, making them ideal as a mode of communication between the
two. I will present our work on discovering a vocabulary of these
attributes in the first place and on enhancing the communication power of
these attributes by using them relatively. We utilize attributes for a
variety of applications including improved image search and effective
active learning of image classifiers.

-- 
Liv Leader
Human Resources Coordinator

Toyota Technological Institute Chicago
6045 S Kenwood Ave
Chicago, IL 60637
Phone- (773) 702-5033
Fax-     (773) 834-9881
Email-  lleader at ttic.edu <jam at ttic.edu>
Web-   www.ttic.edu
<http://www.ttic.edu/>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mailman.cs.uchicago.edu/pipermail/colloquium/attachments/20120209/c1a743ef/attachment.htm