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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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Course Description
This course introduces students to both theoretical algorithms and applications in the fields of image analysis and computer graphics. Basics in image processing, image analysis, visualization, computer graphics and animation will be covered in the first half of the semester, and research articles will be presented and current research issues discussed in the second half. The course should be appropriate for graduate students in all areas and for advanced undergraduates.
Course
Content
The material to be discussed in this 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 (finding object boundary), registration (aligning multiple images or surfaces), tracking (following object motion trajectory), recognition (recognizing object identity), modeling (statistical learning and modeling of object shape, appearance, deformation, motion, etc.), 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. Collaboration and group final projects are encouraged and the groups can choose which deformable object they want to model and animate – face, heart, fluid, cloth, cell, and more!
Administrative
Information
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Lectures: |
TTh 9:20-10:35am at Whitaker Lab 270 |
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Instructor: |
Xiaolei (Sharon) Huang; Mohler Lab 322; 610-758-4818; |
xih206 AT lehigh.edu |
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Office hours: Tuesday 3-5pm; or by appointments (send me an email) |
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Course webpage: |
http://www.cse.lehigh.edu/~huang/Spring07/ImageAnalysis_Graphics.html |
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Blackboard
resources: Announcements, Lecture notes,
Prerequisites
While having taken one of the
following courses will make you immediately qualify,
· CSE 397/497: Real-time Image Processing for Autonomous Robot Systems
· CSE 326/426 Pattern Recognition
they are not required. Make an appointment with the instructor and ask for permission if you want to take the course without any of prerequisites above. You should have a reasonably good understanding of linear algebra, and a basic understanding of differential equations and statistics. You should be fluent in C/C++ and experience in Matlab programming will also help.
Textbook
There will be no single text. Selected articles, book
chapters, and course notes will be made available online.
Grading
Grading will be based on two programming assignments, participation in paper discussions and presentations, and a final class project on deformable object modeling and animation. Collaboration and group final projects are encouraged but must be coordinated through the instructor.
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Assignments |
40% |
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Project |
40% |
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Paper seminar participation |
20% |