CVPR'99 Tutorials Program
 
                          June 21-22, 1999
                      Colorado State University
                     Fort Collins, Colorado, USA
 
                            Web Site:
          http://www.cs.colostate.edu/~cvpr99/worktut.html
 
 
 A total of five tutorials will be held in conjunction with the 1999
 IEEE Computer Vision and Pattern Recognition Conference.  The
 tutorials program spans the two days before the main CVPR'99
 conference.
 
 PROGRAM
 
   Monday, June 21st, 1999
     M1. 3D Photography (9:00am - 5:00 pm)
         S. Seitz, B. Curless, P. Debevec, M. Levoy, J.-Y. Bouguet
     M2. Automated Biometrics (8:00am - 12:00pm)
         N. Ratha, A. Senior, R. Bolle
     M3. Multiscale Geometric Image Analysis: Scale-Space Theory 
         (1:30pm-5:30pm)
         B. Romeny
 
   Tuesday, June 22nd, 1999
     T4. Multiple View Geometry (9:00am - 5:00pm)
         R. Hartley, A. Zisserman
     T5. Video computing (8:00am - 12:00pm)
 	M. Shah
 
 REGISTRATION
   Tutorial registration is in the form of One-day or Two-day Tutorial
   Passports. Passports include admission to any of the tutorials
   offered on a single day for a One-day Passport, and on both days
   for a Two-day Passport. To register for tutorials, please use
   the CVPR'99 registration forms. These can be obtained online from
       http://www.cs.colostate.edu/~cvpr99/registration.html
 
 TUTORIAL ABSTRACTS
   M1. 3D Photography 
      Organizers: S. Seitz (CMU), B. Curless (U. Washington-Seattle)
      Additional speakers: P. Debevec (U. California-Berkeley)
 		          M. Levoy (Stanford), J.-Y. Bouguet (CalTech)
   This course provides an introduction to 3D photography: the process of
   using cameras and light to capture the shape and appearance of real
   objects.  Methods include both passive and active vision techniques
   ranging from stereo, structure from motion, and photogrammetry to
   imaging radar, optical triangulation, and interferometry. The course
   introduces these fundamental methods, provides in-depth analysis of
   several emerging techniques, and concludes with a field study:
   capturing 3D photographs of Michelangelo's statues.
 
   M2. Automated Biometrics 
      Organizers: N. Ratha (IBM), A. Senior (IBM), R. Bolle (IBM)
   This tutorial will address many research as well as practical issues
   in automated biometrics. The underlying pattern recognition and
   computer vision techniques will be reviewed. The state of the art in
   fingerprint, face, iris and speaker identification will be
   presented. Issues in integrating biometrics and representative
   applications will also be discussed.
 
   M3. Multiscale Geometric Image Analysis: Scale-Space Theory
      Organizer: B. Romeny (Utrecht U.)
   The tutorial focuses on multiscale image analysis, its relation to
   human vision, and the differential structure of images in a modern,
   physics based approach. The course is an introduction and overview of
   the field of Gaussian scale-space theory, for computer scientists at
   the graduate level. Goal is primarily to give an intuitive notion of
   the important physics and mathematics involved, and to give a wide
   range of instructive applications
 
   T4. Multiple View Geometry
      Organizers: R. Hartley (GE), A. Zisserman (Oxford U.)
   The key problem to be discussed is the reconstruction of scenes from
   multiple images. Emphasis will be on an approach using uncalibrated,
   or partially calibrated cameras and will be directed to a beginning
   and intermediate-level audience.  The aim of this tutorial is twofold:
    1. To introduce the key ideas in two, three and N-view camera
        geometry. This will include the fundamental matrix for two
        views; the trifocal tensor for 3 views; projective
        reconstruction from two or more views; auto-calibration from
        two or more views.
    2. To describe algorithms for computing these relations.  
   The tutorial will include numerous laptop demonstrations of these
   relations including "live" computations from images.
 
   T5. Video Computing
     Organizer: M. Shah (U. Central Florida)
   During the last three decades, computer vision researchers have worked
   on methods for analyzing sequences of images (video). This work has
   mainly focussed on measurement of 2D motion (e.g., optical flow), 3D
   motion (structure from motion), tracking and scene change detection.
   Recently, there has been growing interest in recognition of motion
   from video sequences. The progress has been made in developing several
   working systems for recognizing hand gestures, human activities and
   behaviors, lip movements, and facial expressions. Interesting work
   also has been reported on video mosaics, video phones, video
   synthesis, video abstraction and retrieval.  This tutorial will
   provide an in depth introduction to various aspects of video. The
   participants will be able learn important algorithms (with
   implementation details) in video understanding. The video
   demonstrations of key systems will be presented, and pointers to the
   recent papers on this topic will be provided.
 
 FOR MORE INFORMATION
 
 For detailed outlines of each tutorial, please check the CVPR'99
 tutorials web page at http://www.cs.colostate.edu/~cvpr99/worktut.html