Week of March 29 - April 2

Monday, March 29

 2:30 GROUPS AND GEOMETRIES SEMINAR  - Room 459 MSC
      Sergey Shpectorov, Mathematics and Statistics, BGSU 
      "Orthogonal and symplectic groups and geometries"

 3:30 ANALYSIS SEMINAR  - Room 459 MSC
      Neal Carothers, Mathematics and Statistics, BGSU
      "The work of William Timothy Gowers, 1998 Fields Medalist, continued"

Tuesday, March 30

 3:30 FACULTY MEETING  - Room 459 MSC
      Annual evaluation procedures 

Wednesday, March 31

 2:30 GROUPS AND GEOMETRIES SEMINAR  - Room 459 MSC
      Sergey Shpectorov, Mathematics and Statistics, BGSU
      "Orthogonal and symplectic groups and geometries"
                                                             
 3:30 ALGEBRA SEMINAR  - Room 459 MSC
      A. A. Ivanov, BGSU and Imperial College, London
      "Y-groups"
      
Thursday, April 1

 3:15 Coffee
 3:45 COLLOQUIUM  - Room 459 MSC
      Kanti Mardia, University of Leeds, England
      "Statistical shape analysis and its applications"
      Abstract: Objects are everywhere - natural and man-made.  With
        advances in technology, images in 2-D and 3-D provide easily
        accessible information on objects, especially their shapes.
        The field of shape analysis gives methods for the study of the
        shape of the objects where location, rotation and scale
        information can be removed.  Assuming that a shape can be
        described by its landmarks, there have been significant
        statistical advances in this decade.  It is in contrast with
        the historical work started in early 1900 by Karl Pearson
        where the measurements were mostly distances, measured by
        using callipers.

        Some statistical aspects of the field have been summarized in
        the recent book on this topic: Dryden and Mardia (1998) Wiley.
        We will describe the latest advances in statistical
        methodology to measure, describe and compare the shape of
        objects.  To make this material generally accessible, we start
        from the analysis of triangles using Bookstein coordinates and
        then proceed to describe Kendall's coordinates Procrustes
        methods, tangent approximations, symmetry in shapes, growth
        data, image warping, averaging and object recognition.  Shapes
        and Direction both live in non-Euclidean spaces, and therefore
        it is not surprising that these two areas share similar types
        of strategies in theory and practice.  However, shape space is
        more complex than directions.

        Practical examples will be given from various fields including
        medical imaging, face analysis and biology.  Open problems in
        the field will be also highlighted.