Announcement

Join the MS Teams group for this lecture to receive announcements. The lecture uses a hybrid format. You can attend in-person in the lecture hall, or join virtually via Teams.

Overview

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

Niklas Mennig

Exam

The final written exam takes place on 22.07.2022 from 10:00 to 12:00

Pre-requisites

  • Programming experience with C++
  • Basic vector math (dot product, cross product, …)

The advanced concepts taught in this course build on the basic techniques that are part of our Computer Graphics core lecture. But the RIS course is self-contained and can be followed without that background.

Lectures and assignments

Date Lecture - Instructor Resources
14.04.2022 Introduction and Rendering equation

Gurprit Singh

18.04.2022 Holiday
21.04.2022 Radiosity

Philipp Slusallek

25.04.2022 Monte Carlo path tracing

Gurprit Singh

28.04.2022 canceled

Gurprit Singh

02.05.2022 Advanced sampling and Spatio-temporal sampling

Gurprit Singh

05.05.2022 Volume rendering

Gurprit Singh

09.05.2022 Bidirectional path tracing

Philipp Slusallek

12.05.2022 Virtual point lights

Philipp Slusallek

16.05.2022 Markov chain Monte carlo

Philipp Slusallek

19.05.2022 Path guiding

Philipp Slusallek

23.05.2022 Density estimation

Karol Myszkowski

26.05.2022 Holiday
30.05.2022 Vertex connection and merging

Karol Myszkowski

02.06.2022 Radar / Spectral

Alexander Rath & Ömercan Yazici

06.06.2022 Holiday
09.06.2022 AnyDSL

Philipp Slusallek

13.06.2022 HDR and tone mapping

Karol Myszkowski

16.06.2022 Holiday
20.06.2022 Perception

Karol Myszkowski

23.06.2022 Modern display technology

Karol Myszkowski

27.06.2022 Machine Learning for Rendering I

Gurprit Singh

30.06.2022 Machine Learning for Rendering II

Gurprit Singh

04.07.2022 No lecture (EGSR)

egsr.eu

07.07.2022 No lecture (EGSR)

egsr.eu

11.07.2022 Machine Learning for Rendering III

Gurprit Singh

14.07.2022 Machine Learning for Rendering IV

Gurprit Singh

18.07.2022 Wrap-up

Philipp Slusallek

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: