Applied Computer Graphics 4860-1084

Lecture at graduate school of information science and technology in the university of Tokyo, spring semester, 2022

ITC-LMS (for Slack and GitHub Classroom invitations):

https://itc-lms.ecc.u-tokyo.ac.jp/lms/course?idnumber=20224860-10840F01

Instructor

Dr. Nobuyuki Umetani

email: umetani@ci.i.u-tokyo.ac.jp
url: http://www.nobuyuki-umetani.com/
lab's web page: https://cgenglab.github.io/labpage/en/

Time

Monday 3rd period, 13:00pm - 14:30pm

Course Description

Computer graphics is a technology to computationally represent objects' geometry, appearance and movement. This course is an introduction to the techniques generally seen in computer graphics. The aim of the course is to get familiar with applied mathematics such as linear algebra, vector analysis, partial differential equations, numerical analysis and optimization through the topics in computer graphics. There are C++ programming assignments to acquire research-oriented graphics programming skills such as OpenGL, Eigen matrix library, Git and cmake.

Topics:

affine transformation & homography
character animation (forward & inverse kinematics)
visualization (rasterization / ray casting)
optimization ( continuous optimization / dynamic programming )
parametric curves & surfaces
variational mesh deformation
grid-based fluid simulation

Lecture Schedule

Day	Topic	Assignment	Slide
(1) Apr. 11	Introduction graphics pipeline		[3]
(2) Apr. 18	Coordinate transfrormation barycentric transformation	task00	[4] , [5]
(3) Apr. 25	Coordinate transformation2	task01	-
(5) May 2	Rasterization	task02	[6]
(4) May 9	Ray Casting I	task03	[7]
(6) May 16	Ray Casting II	task04	[8]
(7) May 23	Parametric curves / surfaces	task05	[9]
(8) June 6	Character deformation	task06	[10], [11]
(9) June 13	Optimization	task07	[12]
(10) June 20	Laplacian mesh deformation	task08	[13]
(11) June 27	Guest lecture by Dr. Ryoichi Ando	-	-
(12) July 4	Grid-based Fluid Ⅰ	task09	[14]
(13) July 11	Grid-based Fluid Ⅱ	-	[15]

Grading

20% lecture attendance
- Attendance is counted based on writing a secret keyword on LMS. The keyword is announced for each lecture.
80% small assignments
- see below

Assignemnts

There are many small programming assignments. To do the assignments, you need to create your own copy of this repository through GitHub Classroom.
These assignments need to be submitted using pull request functionality of the GitHub. Look at the following document.

How to Submit the Assignments

Task ID	Title	Thumbnail
task00	build C++ Program with CMake
task01	2D Homography Transformation
task02	GLSL Vertex Shader (Fisheye Lens)
task03	GLSL Fragment Shader (Sphere Tracing / SDF)
task04	Importance Sampling (Ambient Occlusion)
task05	Rasterization of Cubic Bézier Curves (Sturm's Method)
task06	Linear Blend Skinning (Articulated Rigid Body, Inverse Binding Matrix)
task07	Inverse Kinematics (Levenberg–Marquardt method)
task08	Laplacian Mesh Deformation (Quadratic Programming, Sparse Matrix)
task09	Poisson Image Editing((Gauss-Seidel method, pybind11))

Policy

Do the assignment by yourself. Don't share the assignments with others.
Don't post the answers of the assignment on Slack
Late submission of an assignment is subject to grade deduction
Score each assignment will not be open soon (instructor needs to adjust weight of the score later)

ketaro-m / acg-ketaro-m

readme