Syllabus

Lecture	Date	Topic	(Primary) Source
0	23 Jan 2002	Administrivia; overview of CG	FVFH Preface, Chapter 1
1	28 Jan 2002	Review of basics 1: math foundations	FVFH A.1-A.4
2	30 Jan 2002	Snow day	-
3	04 Feb 2002	Review of basics 2: transformations	FVFH A.5-A.7, 10; HB 11
4	06 Feb 2002	Review of basics 3: interfaces	FVFH 2-3; HB 12
5	11 Feb 2002	Basic scan conversion; 3D viewing pipeline	FVFH 3-4
6	13 Feb 2002	Projections and clipping	FVFH 6
7	18 Feb 2002	OpenGL intro / review and projections	FVFH 5-6
8	20 Feb 2002	3-D clipping; Splines: basics, Bézier	FVFH 11.1-11.2.2, HB 10.6-8
9	25 Feb 2002	Splines: B-splines, NURBS, surfaces	FVFH 11.2.3-11.3, HB 10.9-13
10	27 Feb 2002	3D graphics data structures, shading intro	FVFH 12.1-12.5
11	04 Mar 2002	Photorealism in CGI/CGA, basic CSG	FVFH 12.6-12.10, 20.2
12	06 Mar 2002	Visible surface data structures / algorithms	FVFH 15.1-15.2, HB 10
13	11 Mar 2002	Midterm review	FVFH 14, 15.3-15.9
14	13 Mar 2002	Midterm exam	Focus: 5-6, 11, 15-16
15	25 Mar 2002	Illumination: flat, Gouraud, Phong, etc.	FVFH 15.10, 16.12
16	27 Mar 2002	Illumination models: ray tracing	FVFH 16.13-16.14
17	01 Apr 2002	Visual display of quantitative info
18	03 Apr 2002	More visual display of quantitative info	Tufte, 1992, FVFH 9.1-9.4
19	08 Apr 2002	Envisioning information	Tufte, 1990, FVFH 9.5-9.6
20	10 Apr 2002	Visual explanations; project review	Tufte, 1997, FVFH 10.1-10.2
21	15 Apr 2002	Color; OpenGL Q&A	FVFH 13-14
23	17 Apr 2002	Special topic: fractal systems	FVFH 20.3, VisionDome
24	22 Apr 2002	RenderMan tutorial	VisionDome
25	24 Apr 2002	Animation-fest; RenderMan / raytrace Q&A	FVFH 16, 21
26	29 Apr 2002	Animation-fest; more on fractals	FVFH 21
27	01 May 2002	Animation-fest; L-systems	Lindenmayer handout
28	06 May 2002	Projects I, PBM	FVFH 20
29	08 May 2002	Projects II, particle systems	FVFH 20
30	10 May 2002	Final review; projects due	FVFH 5-7, 9, 11-16, 21

FVFH: Computer Graphics, 2^nd edition, J. D. Foley, A. vanDam, S. K. Feiner, and J. F. Hughes

HB: Computer Graphics, 2^nd edition, D. D. Hearn and M. P. Baker

Class Resources

Web pages

· Official class page: http://www.kddresearch.org/Courses/Spring-2002/CIS736

· Instructor’s home page: http://www.cis.ksu.edu/~bhsu

Note: It is the student’s responsibility to be aware of class announcements and materials posted on the official class page, so please check it frequently.

Class web board

· URL: http://groups.yahoo.com/group/ksu-cis736-spring2002/

· Primary purpose: for class discussions (among students and with instructor)

Note: Postings on the web board will tend to get a more rapid response from the instructor than e-mail, besides which, they are sometimes of benefit to fellow students.

Homework Assignments and Course Project

Homework assignments will be given out 2 to 3 weeks apart, for a total of 5. Your lowest score will be dropped (see below). Three of these homeworks will be programming-based, two will be written.

Type (do not hand-write) homeworks; handwritten solutions are worth 0.8 credit.

For programming assignments and the course project, you are permitted to use your choice of a high-level programming language (C++ and Java are strongly preferred; consult the instructor if you intend to use any other programming language). You must, however, use a development environment that is available to the CIS department. Consult the class web page for approved compilers.

For graduate students and advanced undergraduates interested in working on a class project, you may elect an additional 1 hour of credit as a section of CIS 798 (Special Topics in Computer Science) and either turn in a term paper or work on an extension of the course project or a small-scale independent study project. Suggested project topics and guidelines will be posted on the course web page. Examples include: an animation project; a photorealistic rendering project; rendering one or more scenes using techniques such as ray tracing and radiosity; an experiment with fractal image synthesis or compression; an in-depth comparison of computer-aided design (CAD) or statistical data visualization techniques studied in the course; or improving an existing illumination model or analyzing it formally.

No-Cheating Policy

Cheating consists of misrepresenting another’s work or knowledge as your own. It includes not only copying of test answers, but plagiarism of another person’s written material. While you are encouraged to discuss class material, homework problems, and projects with your classmates, the work you turn in must be entirely your own. For homework assignments, this means that if you work together with a fellow student, you should still produce the final, written material from your own notes and individual work, rather than from common notes that you produced together. You should follow similar guidelines for programming assignments and individual projects; while reuse of previously developed source codes may be permitted in these cases (provided you acknowledge the authors appropriately), you must not use directly use code developed by fellow students. Please consult the University honor code (http://www.ksu.edu/honor) for further guidelines on ethical conduct, and understand the regulations and penalties for violating them.

The codes that you are permitted to use on certain assignments may be limited, beyond the specifications of plagiarism standards. When in doubt about whether you may use a particular program on a written or programming assignment, consult the instructor first. My objective is to help you learn as much as possible from the assignments; sometimes this means that I want you to use existing code and sometimes I will prefer for you to develop it yourself, to better understand the techniques.

Grading

Credit for the course will be distributed as follows:

Component	Quantity	Low Scores Dropped	Points Each (Out of 1000)	Value
Homework (Written/Programming Assignments)	5	1	50	20%
Paper Reviews and Commentaries	3	0	50	6%
Midterm Exam (Closed Book)	1	0	150	15%
Course Project	1	0	300	25%
Final Exam (Open Book/Notes)	1	0	250	20%

Homework and exams may contain extra credit problems.

Late policy: Homeworks are due at 5:00pm on Fridays; you may request an extension to the following Monday if you need one by the due date (but I recommend you do not take this option). 10% credit will be deducted for each day the assignment is late past 5:00pm that Monday. There will be no additional extensions!

Letter grades will be assigned based on the distribution of raw scores (“curved”). Undergraduate and graduate students will be graded on the same curve. Acquiring 85% of the possible points, however, guarantees an A; 70%, a B; 55%, a C. Actual scales may be more generous than this if called for, but are not expected to be.

If you elect to take an additional CIS 798 project option (for 1 hour of credit), your grade for CIS 736 will still be assigned based only on the above components. The additional project component will be graded separately (as CIS 798) and weighted proportionately.

Paper Reviews and Commentaries

An important part of learning about computer graphics and visualization systems, whether for research or development applications, is understanding the state of the field and the repercussions of important results. The readings in this course are designed to give you not only a set of tutorials and references for machine learning tools and techniques, but to demonstrate the subject as a unified whole, and to encourage you to think more deeply about the practical and theoretical issues.

Toward this end, I have selected 4 papers out of those in your (2) course notes packets. The first 2 of these are in the first packet and the last 2 are in the second. Before you come to lecture on the dates indicated on the class calendar, you should submit (by e-mail to the instructor) a short review of, and commentary on, the assigned paper. This commentary need be no longer than 2 pages (though you can go up to 3 pages if you feel you have something meaningful to add).

This review is an important part of the course, because it can:

· help you to review and rehearse material from lecture

· bring to light questions that you may have about the material

· improve your ability to articulate what you have learned

· help guide the lecture/discussion

· help you to think about working on projects (implementations or research) in this field

Here are some guidelines on writing the reviews:

1. Try to be brief and concise.

2. Concentrate on pointing out the paper’s main strengths and flaws, both in content (key points, accuracy, impact/implications, deficiencies) and in presentation (organization, clarity/density, interest). Try not to merely summarize the paper.

3. Some questions to address (typically a couple in each paper):

· Is the paper of sufficiently broad interest? What do you think its intended audience is? To what audience do you think the paper is significant?

· What makes the paper significant or insignificant?

· How could the presentation be improved to better point out important implications?

· Is the paper technically sound? How so, or in what areas is it not entirely sound?

· What novel ideas can we pick up (about the topics covered in lecture) from the paper?

4. Comment on how the paper (or the topic) affects your own work. How is it relevant (or irrelevant) to you?

5. How might the research be improved in light of how the field has progressed since it was published? Some of these papers were catalysts for research in their areas, so it is sometimes infeasible to second-guess their authors; but comment on what could be done better today.

Paper reviews are late (worth 0 credit) after midnight of the day of the lecture when they are due (i.e., you must submit them before 12:00am Saturday).

Do not plagiarize. It is relatively easy to detect plagiarism of material from the paper itself, related references, and paper reviews of classmates! Again, refer to http://www.ksu.edu/honor for regulations and further guidelines on academic honesty.