Salta al contenuto principale della pagina

COMPUTER GRAPHICS

CODE 109186
ACADEMIC YEAR 2022/2023
CREDITS
  • 6 cfu during the 1st year of 10852 COMPUTER SCIENCE (LM-18) - GENOVA
  • SCIENTIFIC DISCIPLINARY SECTOR INF/01
    TEACHING LOCATION
  • GENOVA
  • SEMESTER 2° Semester

    OVERVIEW

    This course gives the fundamentals of Computer Graphics, exploring the two main approaches based on ray tracing and on rasterization. The course includes theory lectures in class, practical homework, and a final project. The practical part is fully given in C++ vanilla, without using any external library, in order to unravel the inner structure of Computer Graphics programs.

    AIMS AND CONTENT

    LEARNING OUTCOMES

    Learning the theoretical and methodological fundamentals of Computer Graphics

    PREREQUISITES

    Linear algebra: vectors, matrices, linear transformations. 

    Imperative programming

    TEACHING METHODS

    In presence classes for theory. Autonomous work by students for homework & final project.

    SYLLABUS/CONTENT

    Linear algebra: Vectors, matrices, and related operations; coordinate frame, change of frame; linear systems; geometric interpretations.

    Images: vector and raster; output devices; image coordinates; color spaces; image formats.

    Ray tracing: parallel and perspective projection; basic geometric intersections; shading: diffuse, specular, and ambient; shadows, reflections, and refractions.

    Spatial data structures: queries and classification; Spatial indexes: regular grid, kd-tree, quadtree/octree, BSP; Primitive sorting techniques: Bounding Volume Hierarchies; Geometric proxies: sphere, capsule, half-space, AABB, OABB, convex and general polyhedron; collision detection strategies: static, dynamic.

    Procedural synthesis: procedural noise; Perlin noise; color maps; implicit modeling: combination of distances and angles.

    Implicit solid modeling: CSG; Rendering implicit models: ray marching; Explicit meshing of implicit models: marching squares/cubes; Implicit modeling in additive manufacturing.

    Geometric transformations: linear transformations: scaling, rotation, and shearing in 2D; translation; affine transformations and algebra; lines in the affine space; affine sum; the affine space; homogeneous coordinates; scale, rotation, and translation in homogeneous coordinates in 2D and 3D; concatenation of transformations; generic rotations about the origin; Euler coordinates; Euler-axis angle; Transformations of normals; 

    Viewing transformations: pipeline of transformations; viewport transformation; orthographic projection; camera transformation; change of frame; examples; composition of transformation and transformation matrices. 

    Rasterization theory: canonical view volume and pixel grid; implicit shape representation and detection of pixels inside a shape; point-in-triangle test; edge function; barycentric interpolation; triangle rasterization; interpolation of attributes;  clipping; depth sorting; z-buffering; super-sampling anti-aliasing. 

    Rasterization implementation: GPU, content creation, window manager, CPU and GPU memory and bus, OS-specific aspects. Software rasterization: rasterization pipeline, vertex input, presentation of a software rasterizer: rasterization of lines; shaders; rasterization pipeline; attributes; uniforms; vertex attributes and color interpolation; view transformation and preservation of aspect ratio; depth test.

    Picking through ray casting.

    Perspective transformations: perspective projection; extension of homogeneous coordinates and of the affine space; perspective division; perspective projection from frustum to parallelepiped; composition with the orthographic projection; aperture and aspect ratio; perspective division for interpolation of attributes.

    Texture mapping: examples of color mapping, bump mapping, and displacement mapping;  UV mapping and texture lookup; problems with seams and distortion; resampling: magnification and minification; derivatives in screen space; nearest filtering and bilinear filtering; Moire patterns; mipmapping.

    View transformations: order of transformations; modeling transformations: how to place different objects; scene graph; stack of matrices; placing the camera; orbiting camera; camera on a car (POV); object viewer; Euler angles; trackball; implementation with quaternions.

    RECOMMENDED READING/BIBLIOGRAPHY

    Material and references provided by the instructors

     

    TEACHERS AND EXAM BOARD

    Exam Board

    ENRICO PUPPO (President)

    CLAUDIO MANCINELLI

    PAOLA MAGILLO (President Substitute)

    LESSONS

    LESSONS START

    Monday, Feb. 27th, 2023, 2:00PM

    Class schedule

    All class schedules are posted on the EasyAcademy portal.

    EXAMS

    EXAM DESCRIPTION

    Homework (mandatory)

    Project (single or teamwork)

    Oral exam

    ASSESSMENT METHODS

    The homework and the project will be evaluated for the correctness and efficiency of the solution.

    The oral exam will usually concern the part of the syllabus not related to the specific topic covered with the project. 

    Exam schedule

    Date Time Location Type Notes
    09/06/2023 09:00 GENOVA Esame su appuntamento
    08/09/2023 09:00 GENOVA Esame su appuntamento
    12/01/2024 09:00 GENOVA Esame su appuntamento