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CSE
398/498:011: Image
Analysis and Graphics |
Spring 07 |
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Computer Science and Engineering Department |
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Office: Mohler Lab 322
Phone: (610) 758-4818
Email: xih206 AT lehigh.edu
Office hours: Tue. 3-5pm; or by appointment (send me an email)
CSE 398/498 Section 011
Spring 2007
TTh 9:20-10:35am
Whitaker Lab 270
http://www.cse.lehigh.edu/~huang/Spring07/ImageAnalysis_Graphics.html
Blackboard usage: Announcements, Lecture notes, Assignments, Email lists, Discussion board
This course introduces students to both theoretical algorithms and applications in the fields of biomedical image analysis, computer vision, and computer graphics. The material to be discussed in the course falls into two categories: foundations and applications. First, a look at the variety of images and graphics, from pictures and videos to biomedical or satellite images, from computer generated images to animated movies, is to give students an idea about the wide application domains of imaging and graphics. Second, a set of problems that serve as foundations to most image analysis tasks will be presented and state-of-the-art algorithms addressing these problems will be discussed. In particular, the problems of interest include segmentation, registration, tracking, recognition, modeling, as well as quantification and statistical analysis. Third, the students will also be exposed to computer graphics (CG) techniques that can be used to model object geometry, to animate, to render, and to visualize information extracted from real-world images. Deformable models, Physically-based simulation, data-driven simulation, interactive simulation, and 3D image visualization are several topics of study. As a conclusion to the course, the students will work on a class project to model and animate a deformable (non-rigid) object. The project aims to walk the students through a whole spectrum from raw images of a deforming object, to extracting and abstraction of its properties, and finally to its visualization, even synthesis, by computer graphics and animation.
Reference Books
Computer
Vision
Linda G.
Shapiro, George C.
Stockman
Prentice Hall, 2001
Introductory Techniques for 3-D Computer Vision
Emanuele Trucco, Alessandro Verri
Prentice Hall, 1998
Physics-Based Deformable
Models: Applications to Computer Vision, Graphics and Medical Imaging
Dimitris Metaxas
Kluwer Academic Publishers, 1996
Handbook of Medical Imaging, Volume 2. Medical Image Processing and Analysis
Jacob Beutel (Editor), M. Sonka (Editor)
SPIE-International Society for Optical Engine, 2000
Geometric
Partial Differential Equations and Image Analysis
OpenGL Programming Guide,
2nd Edition,
Mason Woo, Jackie Neider, Tom Davis,
Addison Wesley, 1997
Computer Graphics with OpenGL, 3rd edition,
Donald Hearn and M. Pauline Baker,
Pearson Prentice Hall, 2004
Computer Graphics using OpenGL, 3rd edition,
F.S Hill Jr, S. M. Kelley
Prentice Hall, 2007
Interactive
Computer Graphics: A Top-Down Approach with OpenGL, 4th edition
Edward Angel,
Addison Wesley, 2005
ISBN 0321321375
Suggested Software Libraries:
Biomedical Image Analysis
o NIH Image J
http://rsb.info.nih.gov/nih-image/about.html
o NLM Insight Segmentation and Registration Toolkit
General
o Matlab from Mathworks,
http://www.mathworks.com/products/matlab/
http://www.mathworks.com/products/image/
Image Processing, Computer Vision
o Intel OpenCV library
http://www.intel.com/technology/computing/opencv/
o Others
http://www.efg2.com/Lab/Library/ImageProcessing/SoftwarePackages.htm
Computer Graphics
o OpenGL resources
http://www.cse.lehigh.edu/~huang/CSE313_Fall06/Resources.html
o Computer Graphics related software packages available on the net
http://www.acm.org/tog/Software.html
o A C++ library implementing a Physical modeling framework described in the book “Physically-Based Modeling for Computer Graphics: A Structured Approach” by Ronen Barzel
http://sourceforge.net/projects/physics
All projects are due at 12 midnight on the due date. Directions on how to submit projects will be announced on Blackboard under Assignments.
Every assignment must be completed in order to receive a grade for the course. 10 points (out of 100) will be taken off for each day that an assignment is turned in late. In other words, 10 points will be taken off if the assignment is turned in 24 hours after the due time, and so on.
You have a fair amount of freedom in choosing which project to work on for this course. You can choose to work alone or work in a group. Collaboration and group final projects are encouraged but must be coordinated through the instructor. For a group project, it should be made clear in the project report which student is responsible for which part of the project so that individual performance can be evaluated on top of group performance evaluation. Please refer to the "Collaboration Policy" statement for examples of what is and what is not unfair collaboration. If we have reason to believe you have not done what you said you did, we reserve the right to give you a brief oral exam about the assignment, and adjust your grade accordingly. Should you have any questions about this, please ask the instructor.
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Dates |
Topics |
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Week 1 |
1/16, 1/18 |
Introduction,
Image Processing I |
· Handouts from the book “Introductory Techniques for 3-D Computer Vision”, by E. Trucco & A. Verri · Fundamentals Image Processing · Documentation for Suggested Software Libraries |
Week 2 |
1/23, 1/25 |
Image Processing
II, Differential Equations |
· Handouts form the book “Computer Vision” by L. G. Shapiro & G. C. Stockman ·
o http://www.pixar.com/companyinfo/research/pbm2001/ |
Week 3 |
1/30, 2/1 |
Student
Presentations, Model-guided Image Segmentation |
· Active Contour Models
· Region Growing Segmentation
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Week 4 |
2/6, 2/8 |
Image Segmentation, Statistical Shape and Appearance Models |
· Mean Shift
· Intelligent Scissors/Live Wire · Principal Component Analysis |
Week 5 |
2/13, 2/15 |
Optimization, Overview of recognition, detection, registration, tracking |
· Optimization, Gradient Descent · Active (Statistical) Shape and Appearance models · Overview of object recognition, detection, registration, motion tracking |
Week 6 |
2/20, 2/22 |
Cell Image Analysis, Graphics Basics |
· Guest lecture · Cell Image Analysis · Graphics Basics |
Week 7 |
2/27, 3/1 |
Transformations, Polygon Meshes, Curves and Surfaces Research Article Presentations |
· Transformations, Polygon Meshes
· Papers suggested to present:
·
Robust
Real-time Face Detection,
Viola & Jones, ICCV
2001 ·
Rapid
Object Detection using a Boosted Cascade of Simple Features, Viola & Jones,
CVPR 2001
·
Support
Vector Machines for 3D Object Recognition, Pontil & Verri, PAMI 1998 ·
Object
recognition from local scale-invariant features, Lowe, ICCV 1999 ·
Shape
Matching and Object Recognition Using Shape Contexts, Belongie, Malik
& Puzicha, PAMI 2002 ·
Object Class
Recognition by Unsupervised Scale-Invariant Learning, Fergus, Perona
& Zisserman, CVPR 2003 · Conditional Random Fields for Object Recognition, Quattoni, Collins & Darrel, NIPS 2004 |
Week 8 |
3/6, 3/8 |
Spring Break |
No classes |
Week 9 |
3/13, 3/15 |
Transformations, Non-rigid Deformations Research Article Presentations |
· Papers suggested to present:
·
Matching
Shapes, Belongie, Malik & Puzicha, ICCV 2001 ·
A New
Point Matching Algorithm for Non-rigid Registration, Chui &
Rangarajan, CVIU 2003 ·
Distance Functions for
Non-rigid Registration, Paragios, Rousson & Ramesh, CVIU 2003 ·
Alignment
by Maximization of Mutual Information, Viola & Wells, 1997
·
CONDENSATION
– Conditional Density Propagation for Visual Tracking, Isard &
Blake, IJCV, 1998 ·
Kernel-Based
Object Tracking, Comaniciu, Ramesh & Meer, PAMI 2003 ·
A
Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian
Tracking, Arulampalam, Maskell, Gordon & Clapp, IEEE Trans. on Signal
Processing, 2002 ·
Dynamical
Statistical Shape Priors for Level Set based Tracking, Cremers, PAMI 2006 |
Week 10 |
3/20, 3/22 |
Thin Plate Splines, Radial Basis Functions, Free Form Deformations |
· Handouts on Thin Plate Splines and Free Form Deformations · Papers suggested to present:
·
Bookstein, F.
L. "Principal Warps: Thin Plate Splines and the Decomposition of
Deformations." IEEE Trans. Pattern Anal. Mach. Intell. 11, 567-585,
1989. ·
Donato &
Belongie, “Approximating
Methods for Thin Plate Spline Mappings and Principal Warps,” ECCV
2002.
·
Carr, Beatson,
Cherrie, Mitchell, Fright, McCallum & Evans, ,
“Reconstruction
and Representation of 3D Objects with Radial Basis Functions,” in ACM SIGGRAPH, 2001.
·
T. Sederberg
and S. Parry, “Free-Form Deformation of Solid Geometric Models,”
in ACM SIGGRAPH, 1986, pp. 151–160. ·
Nonrigid
Registration Using Free-Form Deformations:Application to Breast MR Images,
Rueckert, Sonoda, Hayes, Hill, Leach & Hawkes, IEEE Trans. on Medical
Imaging 1999. ·
Shape
Registration in Implicit Spaces Using Information Theory and Free Form
Deformations, Huang, Paragios
& Metaxas, PAMI 2006 ·
Skinning Characters
using Surface-Oriented Free Form Deformations, Singh & Kokkevis,
Proc. Of Graphics Interface, 2000. |
Week 11 |
3/27, 3/29 |
Physically based modeling and Interactive Simulation Research Article Presentations |
· Topics o Physically Based Modeling o Physically Based Deformation ·
o http://www.pixar.com/companyinfo/research/pbm2001/ · Lecture Notes, Paper Links by Dr. Doug L. James |
Week 12 |
4/3, 4/5 |
Physically based Modeling and Simulation II Class Project
Proposal Presentations |
· Topics
· Lecture Notes, Paper Links by Dr. Ming C. Lin |
Week 13 |
4/10, 4/12 |
Animation Research Article Presentations |
· Topics:
· Animation papers compiled by Dr. David Brogan |
Week 14 |
4/17, 4/19 |
Rendering and Realism Research Article Presentations |
· Topics
· Suggested Papers to present:
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Week 15 |
4/24, 4/26 |
Final Project
Presentations |
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5/1 ~ 5/9 |
Final Exam period |
N/A |
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5/21 |
University Commencement |
N/A |