CSCI 480/580 - Computer Graphics

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• Course webpage (you are here)
• Canvas
• Feedback

Course Overview

In Brief

• CSCI 480: CRN 44067
• CSCI 580: CRN 44071
• Credits: 4
• Instructor: Scott Wehrwein (scott.wehrwein@wwu.edu)
• Syllabus and Course Website: https://facultyweb.cs.wwu.edu/~wehrwes/courses/csci480_22f
• Class meetings:
  • Day/Time: MTWF 9:00am–9:50am
  • Location: AW 305
• Office Hours (in-person in CF 471 or remote by appointment):
  • M 10:00-11:00
  • W 11:00-12:00
  • F 11:30-12:30
  • and by appointment

What

Official Synopsis from the WWU Course Catalog

An introduction to computer graphics with a focus on 3D rendering. Topics include representation and manipulation of 3D geometry, modeling, and rendering using both ray tracing and rasterization.

Unofficial Synopsis from the Instructor

This course will give an introduction to the fundamentals of computer graphics, with a focus on rendering techniques. At the core of computer graphics is the modeling and rendering of synthetic scenes. We will begin by discussing some basic data structures for modeling 3-dimensional objects, then spend the bulk of the middle of the course covering two fundamentally distinct approaches to rendering. Beginning with image-order rendering, we will investigate raycasting, raytracing, and touch on more advanced image-order rendering techniques such as path tracing. We will then move on to object-order rendering, covering the basics of hardware-accelerated rendering using OpenGL and programmable shaders. Along the way, we will make heavy use of mathematics, in particular linear algebra, 3D geometry, and coordinate transformations. As time allows, we will delve into the details of the rasterization algorithms underlying OpenGL, as well as other topics that might include animation, spline curves, parametric surfaces, and global illumination.

Official Course Outcomes

On completion of CSCI 480, students will demonstrate:

• Basic understanding of data structures and techniques for modeling 3-dimensional objects.

• Thorough understanding of basic linear algebra and its applications to computer graphics, including the use of homogeneous coordinates and geometric transformations.

• Basic understanding of the object-order graphics rendering pipeline and its constituent spaces, transformations, and algorithms.

• Basic understanding of how to use a hardware-accelerated 3D rendering library such as OpenGL, including the ability to write simple vertex and fragment shaders.

• Basic understanding of image-order rendering (ray-tracing) fundamentals.

On completion of CSCI 580, students will demonstrate:

• Basic understanding of data structures and techniques for modeling 3-dimensional objects.

• Thorough understanding of basic linear algebra and its applications to computer graphics, including the use of homogeneous coordinates and geometric transformations.

• Thorough understanding of the object-order graphics rendering pipeline and its constituent spaces, transformations, and algorithms.

• Basic understanding of how to use a hardware-accelerated 3D rendering library such as OpenGL, including the ability to write simple vertex and fragment shaders.

• Thorough understanding of image-order rendering (ray-tracing) fundamentals.

Textbook

• Required text: Fundamentals of Computer Graphics, Fourth Edition by Marschner and Shirley. ISBN-10 9781482229394. You may also use the newer Fifth Edition (ISBN-10 9780367505035).

Other References

• Computer Graphics from Scratch by Gabriel Gambetta. Part I on ray tracing is a really nice gentle introduction to ray tracing that may serve as helpful supplemental reading material.
• 3blue1brown is a YouTube channel with great videos that cover linear algebra topics with animated explanations. Chapters 3, 4, 5, and 13, among others, are highly relevant to our course material.
• Peter Shirley’s Ray Tracing in One Weekend is a no-nonsense ray-tracing primer with complete C++ code developed in the text.
• For A2 extensions and/or raytracing-related final projects, Peter Shirley followed up RT1W with Ray Tracing: The Next Week, covering distribution ray tracing, acceleration structures, and volume rendering, and Ray Tracing: The Rest of Your Life covering Monte Carlo path tracing.

Assessment

Grades will be calculated as a weighted average of scores on the following course components, each of which is described in more detail below:

• 30% Programming Assignments
• 15% Written homeworks
• 20% Midterm exam
• 25% Final Project
• 10% Surveys, labs, and participation
• (580 students only) 10% Advanced topic presentations

Notice that the 580 components add up to 110%, which is fitting for graduate students. 580 students’ scores will be scaled by a factor of 10/11 to map them back into the 0-100% range before letter grades are assigned.

The standard letter grade ranges apply (i.e., 90–100% is an A, 80–90% is a B, and so on). The calculated raw percentages may be curved at the instructor’s discretion, but any such curve used will not lower anyone’s grade. “+” or “-” cutoffs will be decided at the instructor’s discretion. Students who demonstrate mastery of the material will get grades in the A range, and it is my goal to give as many A’s as possible.

Programming Assignments

Four programming assignments will be given; some will be done individually, while others will be done in pairs. For each paired assignment, you must work with a different partner.

Written Homework

Approximately 4 short written homeworks will be assigned. The primary focus of these homeworks is to reinforce the mathematics underlying the concepts covered in class and make sure you’re prepared to implement the math in the programming assignments.

Midterm Exam

Since there is no final exam, the midterm exam is given later in the quarter. The midterm will be a take-home exam released on Friday, 11/4 and due by the start of class on Monday 11/7.

Final Project

In place of a final exam, students will complete a final project, which will provide a chance to explore and implement a special topic beyond the basics covered in the programming assignments. Final projects may either be a significant extension of one of the programming assignments, or a standalone implementation on a separate topic. The final project will be done in groups of two or three. You will submit a project proposal by Friday of the 6th full week of class (11/4). Progress will be tracked via two weekly intermediate milestone deliverables. The final project source code, results, and writeup are due on Sunday night preceeding finals week (12/4), and each group will give a brief (5-minute) project presentation during our final exam slot (between 9:00 and 10:00am on 12/5).

Surveys, Labs, and Participation

Many class periods will include group problem-solving exercises, and later in the quarter we will have several in-class labs. Participation in group work, completion of labs, and responses to feedback surveys will be counted towards this component of your grade.

(580 only) Advanced Topic Presentation

Graduate students will work in teams to prepare and lead a class on an advanced topic of their choice during the last week of classes. Typically, the topic of this class will either be an overview of an active sub-area of graphics research, or a deep dive into some topic not covered in lecture. The topic may coincide or overlap with your final project topic, but is not required to. Topics will be proposed and finalized alongside final projects.

Logistics

Course Webpage / Syllabus

The Schedule section of this page will be updated as the quarter progresses with topics, links to lecture slides, code examples, readings, and links to assignment and lab handouts. I suggest bookmarking this page; if you forget the URL and need to find your way back here, you can use link on the Syllabus page in Canvas.

Canvas

We will use Canvas for announcements, grades, and submission of written homework. Programming and Homework Assignments will be linked from both the course webpage and the corresponding assignment on Canvas. Lecture notes and readings will be posted on the course webpage only.

Communication

It is your responsibility to make sure that you promptly become aware of Canvas Announcements as they are posted; Canvas should be configured to send you an email notification by default, but if you are unsure, please come see me in office hours.

Git and GitHub

This course assumes that you have basic familiarity with git. Programming assignments will be completed using git repositories hosted by GitHub and orchestrated by GitHub classroom. You will receive an invitation link to create a repository for each assignment, complete the assignment in a local copy of the repo, and submit by pushing your final changes to GitHub.

Feedback

I take student feedback seriously. I appreciate any feedback you’re willing to give, and I will do my best to act on constructive feedback when possible. I will solicit feedback formally partway through the course, but you are welcome to provide feedback at any time in my office hours, by email, or if you desire anonymity you can use this Google Form.

Schedule

This schedule is tentative and subject to change without notice. Slides/notes, assignments, readings, etc. will be posted and updated here throughout the quarter.

Course Policies

Inclusive Classroom Environment

It is expected that everyone will promote a friendly, supportive, and respectful environment in the classroom, labs, and project groups. Everyone’s participation will be equally welcomed and valued.

Late Work

You have five “slip days” that you may use at your discretion to submit programming assignments or written homeworks late. Slip days cannot be used for the final project. You may use slip days one at a time or together - for example, you might submit each of five assignments one day late, or submit one assignment five days late. Each slip day moves the deadline by exactly 24 hours from the original deadline; if you go beyond this, you will need to use a second slip day, if available.

After your slip days are exhausted, a penalty of .1 * total_assignment_points * floor(hours_late/24 + 1) - that is, 10% of the total points per day late, will be applied.

To use slip days or submit work late, you do not need to let me know ahead of time. For written homeworks, simply submit to Canvas when you are ready, and I will apply slip days according to the submission time, noting the number of slip days used in your feedback. For programming assignments, you will complete your submission by pushing code to Github and filling out a Canvas survey. The submission time of the survey must be after your final push to Github and will be used as the time of submission.

Programming Guidelines

Your programs will be graded on correctness, clarity, and efficiency (in that order).

Correctness:

A correct program is one that always produces the correct output for a given input. Also, a correct program does not produce unintended side-effects. The most effective way to ensure that your program is correct is to test, test, test. Test each component as you introduce it; once you are confident that a component works you can use it in other routines. Try to break your program in testing, and if you succeed, locate the bug and fix it. The better you test your program, the more likely it is to be correct - the more likely it is to be correct, the more likely you’ll earn a good score. Most of your grade will depend on the correctness of your code.

Clarity:

The easier it is to read and maintain your code, the easier it is to locate and remove bugs. Your program should be well organized, appropriately commented, and easy to maintain. To have a well-organized program, design your program thoughtfully and modularly. Think before you code: hacking away blindly leads to ugly, difficult-to-read code. If you do hack away, producing a functional but ugly wall of code, try to clean it up a bit. Make sure that your cleaning does not introduce new bugs.

As for comments, please follow these simple guidelines proposed by Emeritus Professor Osborne:

• A comment at the top of the program states the program’s purpose, the author, and date.
• Each subprocedure is accompanied by a comment that states its purpose and describes pre and post conditions, and mentions any exceptions raised.
• Within a procedure, precede code sections by a comment that says what the section does. This is usually one line long. Occasionally in tricky pieces of code, a comment to the right explains what the code does.
• For each major variable, write a comment to explains its purpose.
• Do not over comment. Brief is best, but not so brief as to be cryptic.

Efficiency:

Your programs should be asymptotically efficient, e.g. checking graph reflexivity should be O(n), insertion into a balanced tree should be O(log n), etc. Do not optimize your code beyond the asymptotic level at the expense of clarity unless the benefits are substantial, and even then do so judiciously, and justify and document your optimizations in comments.

Academic Honesty

Collaboration Policy - Individual Assignments

Individual programming assignments are to be completed independently. Students are welcome to discuss assignments with each other on a conceptual level, but each student should be writing their code independently and without direct help from fellow students. Sharing your code with others or looking at someone else’s code is an explicit violation of this collaboration policy. The best way to be absolutely sure you are collaborating appropriately is follow these two rules:

• Do not discuss programming assignments in the presence of computers - step away from the computer and talk at a whiteboard or sketch ideas on paper instead.
• After any discussion about the assignment, wait an while (watch an episode of Stranger Things, or go to the gym, or work on an assignment for another class) before sitting down to write up your solution.

Automated tools will be used to check your code for plagiarism at the push of a button. They are not fooled by tricks such as changing variable naming and whitespace: in fact, hiding plagiarism is harder than doing the assignment.

Collaboration Policy - Team Based Assignments

For pair programming assignments, the above policy applies to any collaborations with people outside your group. In addition, each partner must be able to independently explain all of the code that your team submits. Pair programming is the recommended way to ensure that this guideline is met, but it is not strictly required. If one team member writes code separately, I suggest having the other team member perform a thorough code review.

University Policies

All University-wide policies apply to this course, including those outlined at http://syllabi.wwu.edu. These policies cover issues including:

• Academic Honesty
• Accommodations
• Ethical Conduct with WWU Network and Computing Resources
• Equal Opportunity
• Finals
• Medical Excuse Policy
• Student Conduct Code