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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

Exam

The final exam will be either written or oral, depending on the number of participants and the Covid situation. The decision will be made in May.

Pre-requisites

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

The advanced concepts taught in this course are used on top of 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
12.04.2021 Introduction

All

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15.04.2021 Rendering equation

Karol Myszkowski

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19.04.2021 Radiosity

Karol Myszkowski

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22.04.2021 Probability theory + MC

Pascal Grittmann

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26.04.2021 BRDFs and path tracing

Gurprit Singh

29.04.2021 Advanced sampling

Gurprit Singh

03.05.2021 Spatio-temporal sampling

Gurprit Singh

06.05.2021 Bidirectional path tracing

Philipp Slusallek

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10.05.2021 Density estimation

Karol Myszkowski

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13.05.2021 Holiday
17.05.2021 Vertex connection and merging

Karol Myszkowski

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20.05.2021 Virtual point lights

Gurprit Singh

24.05.2021 Holiday
27.05.2021 Point-based methods

Gurprit Singh

31.05.2021 Markov chain Monte Carlo

Philipp Slusallek

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03.06.2021 Holiday
07.06.2021 Path guiding

Philipp Slusallek

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10.06.2021 Efficient direct lighting

Philipp Slusallek

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14.06.2021 Volume rendering

Gurprit Singh

17.06.2021 HDR and tone mapping

Karol Myszkowski

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21.06.2021 Perception

Karol Myszkowski

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24.06.2021 Modern display technology

Karol Myszkowski

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28.06.2021 EGSR

egsr.eu

01.07.2021 EGSR

egsr.eu

05.07.2021 Machine Learning for Rendering I

Gurprit Singh

08.07.2021 Machine Learning for Rendering II

Gurprit Singh

12.07.2021 Machine Learning for Rendering III

Gurprit Singh

15.07.2021 Radar / Spectral

Alexander Rath / Ömercan Yazici

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19.07.2021 AnyDSL

Philipp Slusallek

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22.07.2021 Wrap-up

All

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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: