We consider the estimation of diffeomorphic transformations aligning a known
shape and its distorted observation. The classical way to solve this
registration problem is to find correspondences between the shapes and then
compute the transformation parameters from these landmarks. Here we propose a
novel framework where the exact transformation is obtained as the solution of a
polynomial system of equations. The method has been applied to 2D and 3D
medical image registration, industrial inspection, planar homography
estimation,
etc... and its robustness has also been demonstrated. The advantage of the
proposed solution is that it is fast, easy to implement, has linear time
complexity, works without established correspondences and provides an exact
solution regardless of the magnitude of transformation.


Bio:

Zoltan Kato

received the BS and MS degrees in computer science from the Jozsef Attila
University, Szeged, Hungary in 1988 and 1990, and the PhD degree from
University of Nice doing his research at INRIA -- Sophia Antipolis, France in
1994. Since then, he has been a visiting research associate at the Computer
Science Department of the Hong Kong University of Science & Technology; an
ERCIM postdoc fellow at CWI, Amsterdam; and a visiting fellow at the School of
Computing, National University of Singapore. In 2002, he joined the Institute
of Informatics, University of Szeged, Hungary, where he is heading the
Department of Image Processing and Computer Graphics. His research interests
include image segmentation, registration, shape matching, statistical image
models, Markov random fields, color, texture, motion, shape modeling,
variational and level set methods. He has served on several program committees
of major conferences (e.g. Area Chair for ICIP 2008, 2009) and has been an
Associate Editor for IEEE Transactions on Image Processing. He is the President
of the Hungarian Association for Image Processing and Pattern Recognition
(KEPAF) and a Senior Member of IEEE.