This advanced lecture discusses the mathematical concepts and algorithms that are used to simulate the propagation of light in a virtual scene. The topics include Monte Carlo sampling, various Global Illumination algorithms (from the basic Path Tracing algorithm to more advanced algorithms like Vertex Connection and Merging), and HDR imaging. In the practical exercises, the students implement some of the algorithms discussed in the lecture in a lightweight rendering framework.

Instructors

Teaching Assistants

Tutors

Julius Kilger

Pre-requisites

  • Programming experience with C++

Exams

Matriculation number Time
****780 13:00 - 13:30
****464 13:30 - 14:00
****886 14:00 - 14:30
****216 14:30 - 15:00
****595 15:00 - 15:30

Mailing list

  1. Register for this course’s mailing list here.
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Lectures and assignments

Date Lecture - Instructor Slides Assignments
04/09/2019 Intro
Myszkowski
pdf 
04/12/2019 Rendering Equation
Myszkowski
pdf 
04/16/2019 Radiosity
Myszkowski
pdf 
04/19/2019 Holiday
04/23/2019 HDR and Tone Mapping
Myszkowski
pdf  pdf 
04/26/2019 Perception
Myszkowski
pdf 
04/30/2019 Probability Theory
Singh
pdf 
05/03/2019 MC Integration
Singh
pdf 
05/07/2019 No Lectures (Conference)
05/10/2019 No Lectures (Conference)
pdf 
05/14/2019 Modern Display Technology
Hyeonseung Yu
pdf 
05/17/2019 Perceptual Display
Myszkowski
pdf  pdf 
05/21/2019 Advanced Sampling
Singh
pdf 
05/24/2019 cancelled
05/28/2019 BRDFs and Path Tracing
Grittmann
pdf  pdf zip 
05/31/2019 Bidirectional Path Tracing
Slusallek
pdf 
06/04/2019 No Lectures
06/07/2019 Virtual Point Lights
Slusallek
pdf pdf  pdf 
06/11/2019 Density Estimation
Myszkowski
pdf 
06/14/2019 Volume Rendering
Singh
pdf 
06/18/2019 Vertex Connection and Merging
Slusallek
pdf pdf 
06/21/2019 cancelled
pdf zip 
06/25/2019 Path Guiding
Slusallek
pdf pdf 
06/28/2019 Spatio-temporal Sampling
Singh
pdf pdf 
07/02/2019 Machine Learning I (Introduction)
Singh
pdf 
07/05/2019 Machine Learning II (Reconstruction I)
Singh
pdf 
07/09/2019 No Lectures (Conference)
07/12/2019 No Lectures (Conference)
07/16/2019 No Lectures
07/19/2019 Machine Learning III (Reconstruction II)
Singh
pdf 

General Regulations

  • Type: Special Lecture, Practical computer science
  • ECTS: 9 credit points
  • Practical assignments
    • Longer term projects
    • Not a rendering competition as in CG1
  • Assignments can be submitted by groups of up to 2 students.

Literature

The lecture is not bound to a specific book. The following list contains the most important books about image synthesis:

  • Pharr, Jakob, Humphreys, Physically Based Rendering : From Theory to Implementation, Morgan Kaufmann
  • Shirley et al., Realistic Ray Tracing, 2. Ed., AK. Peters, 2003
  • Jensen, Realistic Image Synthesis Using Photon Mapping, AK. Peters, 2001
  • Dutre, at al., Advanced Global Illumition, AK. Peters, 2003
  • Glassner, Principles of Digital Image Synthesis, 2 volumes, Morgan Kaufman, 1995
  • Cohen, Wallace, Radiosity and Realistic Image Synthesis, Academic Press, 1993
  • Apodaca, Gritz, Advanced Renderman: Creating CGI for the Motion Pictures, Morgan Kaufmann, 1999
  • Ebert, Musgrave, et al., Texturing and Modeling, 3. Ed., Morgan Kaufmann, 2003
  • Reinhard, Ward, Pattanaik, Debevec, Heidrich, Myszkowski, High Dynamic Range Imaging, Morgan Kaufmann Publishers, 2nd edition, 2010.
  • Myszkowski, Mantiuk, Krawczyk. High Dynamic Range Video. Synthesis Digital Library of Engineering and Computer Science. Morgan & Claypool Publishers, San Rafael, USA, 2008.

Here is a list of other reference materials you can use, grouped by topic: