2025 (Current Year) Faculty Courses School of Computing Department of Mathematical and Computing Science Graduate major in Artificial Intelligence
Computer Graphics
- Academic unit or major
- Graduate major in Artificial Intelligence
- Instructor(s)
- Suguru Saito
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Class
- -
- Course Code
- ART.T463
- Number of credits
- 200
- Course offered
- 2025
- Offered quarter
- 4Q
- Syllabus updated
- Mar 31, 2025
- Language
- English
Syllabus
Course overview and goals
Computer Graphics consists of useful techniques in various fields, which generate images from various data. In this course, students learn basic knowledge of digital image processing, optics, color vision, geometric algebra to use these techniques efficiently.
Computer Graphics is techniques based on theories in various fields. This course covers fundamental topics of these theories. In addition, practical programming for real time computer graphics is also instructed. Students who attend this course will acquire both knowledge of fundamental theories and practical skills for computer graphics. Assignments require programming skills. Students are strongly expected to have basic programming skills. Sample codes are provided for these subjects.
Course description and aims
The goal of this course is to learn fundamental theories to be required for digital image processing and computer graphics to display 3D objects as color image, and skills to create programs for real time 3D graphics with OpenGL library and Shader Language.
Students will be able to
1) understand the characteristics of image filters in frequency domain,
2)transfer coordinates between color spaces,
3) understand basic equations for CG, and
4)create basic CG programs with OpenGL library.
Keywords
Fourier Transform, Sampling Theory, Image Filter, Color Perception, Color Space, Reflection, Affine Transform, Projection, Graphic Pipeline, Real Time Rendering
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Lecture
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Introduction | |
| Class 2 | Fourier Series and Fourier Transform | Inner product of functions, Relationship between Fourier Series and Fourier Transform |
| Class 3 | Frequency domain and Image domain | Relationship between Operations in Frequency Domain and Image Domain |
| Class 4 | Sampling Theory and Aliasing | Sampling Theory |
| Class 5 | Image filter | Characteristics of image filters |
| Class 6 | primitive data for computer graphics | Description of geometric shape |
| Class 7 | Affine Transform and Projection | Use of Homogeneous Coordinate System |
| Class 8 | Real time CG programing 1 (how to display primitive objects) | OpenGL, implement to display basic 3D shape with reflection |
| Class 9 | Basic of Color Vision | From Spectrum to Color |
| Class 10 | CIE Color Space | CIEXYZ and More Perceptual Uniform Color Space |
| Class 11 | Device Color Space | Definition of Device Color Space, |
| Class 12 | reflection | Specular Reflection, Diffuse Reflection,, BRDF |
| Class 13 | Graphic pipeline | Process Flow of Modern Graphics Hardware |
| Class 14 | Real time CG programing 2 (Scene Rendering) | OpenGL, Shader Language |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
None.
Reference books, course materials, etc.
Handout will be delivered in the class.
Data and sample codes will be uploaded on a web site.
Evaluation methods and criteria
Scored by the reports for several assignments.
Related courses
- None
Prerequisites
Basic programming skills are required.