MS-CS-L Archives

April 2009


Options: Use Monospaced Font
Show Text Part by Default
Show All Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Jyh-Ming Lien <[log in to unmask]>
Reply To:
Jyh-Ming Lien <[log in to unmask]>
Mon, 20 Apr 2009 15:17:18 -0400
text/plain (80 lines)
[Apologies for multiple postings]

Please come and join us tomorrow!

Note that the starting time is *12:30pm*

Note the new location *ENGR 4201*

*    GRAND Seminar
*    Tuesday, April 21, 2009, 12:30 pm
*    Engineering Building Room 4201


Affine Invariant-Based Classification of Inliers and Outliers
for Image Matching


Dan Fleck
Department of Computer Science


This presentation describes a new approach to classify tentative feature
matches as inliers or outliers during wide baseline image matching.
Wide-baseline matching is the process of matching one image to another.
After typical feature matching algorithms are run and tentative matches
are created, our approach is used to classify matches as inliers or
outliers to a transformation model. The approach uses the affine
invariant property that ratios of areas of shapes are constant under an
affine transformation. Thus, by randomly sampling corresponding shapes
in the image pair we can generate a histogram of ratios of areas. The
matches that contribute to the maximum histogram value are then
candidate inliers. The candidate inliers are then filtered to remove any
with a frequency below the noise level in the histogram. The resulting
set of inliers are used to generate a very accurate transformation model
between the images. In our experiments we show similar accuracy to the
standard RANSAC approach and an order of magnitude efficiency increase
using this affine invariant-based approach.

*Short Bio*

Dan Fleck is currently an instructor of Computer Science at George Mason
University (GMU). He earned his B.S. in Electrical Engineering from the
University of Texas at Austin before moving to Northern Virginia. While
working full-time Dan completed his M.S. in Software Engineering from

Currently he is pursuing a doctorate degree in Computer Science. Dan's
doctoral research is in Computer Vision under Dr. Zoran Duric.
Specifcially researching novel approaches to matching images taken at
different viewing angles, locations and scales.

Previously, Dan was a technical lead and project manager at SRA
International. At SRA he led projects ranging from 5 to 50 people for a
variety of government clients. Dan worked within SRA's Health Systems
group, Data Mining Center and most recently as technical lead within the
Advanced Technology Group. Dan continues to serve in an advisory role at

Jyh-Ming Lien
Assistant Professor
Department of Computer Science       [log in to unmask]
George Mason University, MSN 4A5
Fairfax, VA, 22030, USA              tel: +1-703-993-9546