고급 컴퓨터 그래픽스 중앙대학교 컴퓨터공학부 손 봉 수

Course Overview Level : CSE graduate course No required text. We will use lecture notes and on-line materials This course requires C/C++ programming skills Format –Instructor lectures on graphics basics. –Student presentation and discussion on graphics programming & advanced topics –Conducting individual projects and presentation Course Objective –Broad understanding of basic computer graphics –Apply computer graphics knowledge to real graphics programming –Deep experience with recent advanced topics

Graphics vs Vision Computer Vision –Understanding the “content” of an obtained image (usually by creating a “model” of the depicted scene) Computer Graphics –Creating an image from a computer model Image Processing –Processing an image into another form of an image or features 3D Model 2D Image Graphics Vision

Computer Graphics Introduction Imaging : representing 2D images Modeling : representing 3D objects Rendering : drawing 2D images from 3D models Animation : models/scenes deform & move Modeling Rendering Animation

Example Virtual Billiard, 카트라이더

Topics Graphics and Visualization Basics Graphics Programming –CUDA : many-core GPU programming, GPGPU –GUI + Graphics Programming (QT OpenGL programming) –Mobile Graphics (Android OpenGL ES programming) Advanced Topics –Recent papers

Course Information Time : Tuesday 3pm-6pm Class webpage : Instructor Information –Office : – –Office Tel# : –Office Hour : Tuesday 2pm-3pm or by appointment

Graphics Basics Rendering Pipeline Object Representation, Modeling, Transformation Visual Appearance (Lighting, Shading, Material) Texture mapping, bump mapping, … Visibility (Z-buffers, … ), Terrain Visualization Basic Image Processing Photo-Realistic Rendering (Raytracing, …)

Polygonal Model Mesh Representation

Volumetric Model [ volume image ] [ skin surface ] [ bone surface ] F(x,y,z) Isosurface : F(x,y,z) = w w = skin density w = bone density

Cardiovascular Modeling  Research Pipeline 3D Image Acquisition Geometric Modeling Simulation Rendering, Quantitative Visualization cardivascular disease research, medical device design, and surgical planning

Terrain Rendering

Animation Motion Capture Physics Based Animation Sound Processing –3D Sound [SNU MRL lab] [SNU graphics lab] [Stanford graphics lab]

Graphics Programming –QT library –OpenGL –OpenGL ES

Many-core GPU computation CUDA –many-core GPU processing –GPGPU (General Purpose computing on GPU) nVidia GeForce GTX590 : 1024 CUDA cores CPU GPU

Many-core GPU computation GTX 280

Evaluation Grade will be based on –midterm exam (30%) –final exam (30%) –presentation and class participation (30%) –attendance (10%)