CSE 398/498:011:

Image Analysis and Graphics

 

 

 

Spring 07

X. Sharon Huang

Computer Science and Engineering Department

Lehigh University

 

Course Information

Syllabus

Resources

CSE-398/498:011:   Image Analysis and Graphics

Professor Xiaolei Huang

Instructor’s Contact Information

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)

Course Information

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

 

Course Description

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. 

Course Goals

By the end of the semester, students will be able to:

(1)                        write small computer programs to perform basic image analysis, modeling, and visualization tasks.

(2)                        implement advanced algorithms for image analysis, deformable modeling, and simulation.

(3)                        have a basic understanding of challenging research topics in image analysis and graphics.

(4)                        propose solution to a real-world image analysis and simulation problem utilizing knowledge learned in the class, and build an end-to-end (interactive) computer application to tackle the problem.

Books

No Required Text

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

Guillermo Sapiro

Cambridge University Press, 2001

 

OpenGL Programming Guide, 2nd Edition,
Mason Woo, Jackie Neider, Tom Davis,
Addison Wesley, 1997

Online version

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

Physically Based Modeling: Principles and Practice

http://www.cs.cmu.edu/~baraff/sigcourse/, 1997

http://www.pixar.com/companyinfo/research/pbm2001/, 2001

 

Physically-Based Modeling for Computer Graphics: A Structured Approach

Ronen Barzel

Academic Press, 1992

Articles

Related research articles will be posted online, on Blackboard, or given as handouts in class.

Suggested Software Libraries:

      Biomedical Image Analysis

o      NIH Image J

      http://rsb.info.nih.gov/nih-image/about.html

      http://rsb.info.nih.gov/ij/

 

o      NLM Insight Segmentation and Registration Toolkit

      http://www.itk.org/

 

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

 

Expectations

Your preparation, attendance, engagement and participation are all crucial to the success of this class.  In class, I will deliver lectures, demonstrate examples and discuss projects.  I will also invite a few guest lecturers to describe the research background to several projects that you may choose to work on. You will be expected to participate in a variety of activities including asking/answering questions related to reading material, participating in presenting research articles, completing programming assignments, and designing, reporting and implementing the final project on modeling and animating deformable objects.  The course is appropriate for graduate students in all areas and for advanced undergraduates.  Our end goal is for you to understand important theoretical algorithms in biomedical image analysis, computer vision and computer graphics, for you to be able to apply algorithms to real-world applications, to write small- to large- scale computer programs to conduct a research project, and to achieve the goals that motivated you to come to this class in the first place.

Assignments

Over the course of this semester, you will

§       actively participate in-class discussion related to assigned reading material

§       evaluate different project options and software options, and choose one project that you would like to work on; you are encouraged to present your project plan in class or discuss with the instructor out of class.

§       present 1~2 research articles related to the project that you have chosen

§       complete two programming projects related to fundamentals in image analysis, graphics, and deformable modeling.

§       Complete the final research project, and write a project report including the following sections: literature review, methodology, experimental results, discussion and future work. 

Your grade will be determined as follows:

§       Two programming assignments on fundamentals:  20% each, 40% total

§       Paper seminar participation, project proposal and attendance: 20%

§       Final class project and project report: 40%

Policies

Attendance Policy

Regular attendance is required for all scheduled class meetings and the student is responsible for information covered in assigned readings, handouts, discussions and activities.  If you miss class because of an emergency, please notify the instructor by calling or leaving a phone message.  Attendance is worth 5% of your final grade.

Submission Policy

All projects are due at 12 midnight on the due date.  Directions on how to submit projects will be announced on Blackboard under Assignments.

Statement on Late Papers and Missed Exams

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. 

Statement on Students with Disabilities

If you have a documented learning disability, and will be requesting academic accommodation for this class, please contact Dean Cheryl Ashcroft in the Office of the Dean of Students, UC 212, at x84152, or by email at caa4@lehigh.edu.  She will establish the appropriate accommodations for your case.

Collaboration and Academic Integrity

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.

Schedule

Reading materials, lecture notes, project resources will be made available online or on Blackboard. You are responsible to check new announcements, and feel free to use the email list and discussion board for questions.

The following schedule is tentative and is subject to change.

 

Dates

Topics

Readings

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

·        Readings from Baraff & Witkin's "Physically Based Modeling” course notes, SIGGRAPH2001

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

 

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

  • Handouts from the book “Computer Graphics using OpenGL, 3rd edition”, by  F.S Hill Jr & S. M. Kelley

·       Papers suggested to present:

  • AdaBoost

·        Freund, Y., Schapire, R.E.: A decision theoretic generalization of on-line learning and an application to boosting. Journal of    Computer and System Sciences 55, (1997) 119–139

·         Schapire, R.E.: A brief introduction to boosting. In: Proc. of 16th Int’l Joint Conf. on Artificial Intelligence. (1999) 1401–1406

 

  • Object Detection

·        Robust Real-time Face Detection,  Viola & Jones,  ICCV 2001

·       Rapid Object Detection using a Boosted Cascade of Simple Features, Viola & Jones,  CVPR 2001

 

  • Object Recognition

·        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:

  • Shape/Image Matching and Registration

·        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

 

  • Motion Estimation and Tracking

·        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:

  • Thin Plate Splines

·        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.

  • Radial Basis Functions

·        Carr, Beatson, Cherrie, Mitchell, Fright, McCallum & Evans, ,Reconstruction and Representation of 3D Objects with Radial Basis Functions,” in ACM SIGGRAPH, 2001.

  • Free Form Deformations

·        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

 

·        Readings from Baraff & Witkin's "Physically Based Modeling” course notes, SIGGRAPH 2001

o       http://www.pixar.com/companyinfo/research/pbm2001/

·        Lecture Notes, Paper Links by Dr. Doug L. James

o       http://www.cs.cmu.edu/%7Edjames/pbmis/index.html

Week 12

4/3, 4/5

Physically based Modeling and Simulation II

 

Class Project Proposal Presentations

 

 

·       Topics

  • Collision Detection
  • Rigid-body Dynamics
  • Constrained Dynamics

 

·       Lecture Notes, Paper Links by Dr. Ming C. Lin

Week 13

4/10, 4/12

Animation

 

Research Article Presentations

·       Topics:

  • Key framing
  • Inverse Kinematics
  • Behavior based animation
  • Dynamic Simulation

 

·       Animation papers compiled by Dr. David Brogan

 

Week 14

4/17, 4/19

Rendering and Realism

 

Research Article Presentations

·       Topics

  • Ray Tracing, Radiosity, Photon Mapping
  • Volume Rendering
  • Image-based Rendering

 

·       Suggested Papers to present:

Week 15

4/24, 4/26

Final Project Presentations

 

 

5/1 ~ 5/9

Final Exam period

N/A

 

5/21

University Commencement

N/A

 

Communication

Keep me posted about how things are going for you.  Visit during office hours.  Send an email to make an appointment outside of my office hours to discuss about your project.  I will hold extra office or lab hours when a large project is near due.

Welcome to the class!  Please do not hesitate to contact me if you have any questions or concerns.