Lecture Rendering

This course aims to give an overview of basic and state-of-the-art methods of rendering. Offline methods such as ray and path tracing, photon mapping and many other algorithms are introduced and various refinement are explained.

The basics of the involved physics, such as geometric optics, surface and media interaction with light and camera models are outlined.

The apparatus of Monte Carlo methods is introduced which is heavily used in several algorithms and its refinement in the form of stratified sampling and the Metropolis-Hastings method is explained.

At the end of the course students should be familiar with common techniques in rendering and find their way around the current state-of-the-art of the field. Furthermore the exercises should deepen the attendees' understanding of the basic principles of light transport and enable them to write a simple rendering program themselves.

• Rendering theory
  Basic optics, rendering equation, filtering
• Rendering algorithms
  Ray tracing, radiosity, (bi-directional) path tracing, Metropolis light transport, precomputed radiance transfer, (stochastic progressive) photon mapping, irradiance caching, path space regularization, vertex connection and merging
• Acceleration techniques
  Spatial hierarchies, sampling strategies,
• Surface representations
  BRDF models: Lambert, Phong, Oren-Nayar, Cook-Torrance, Ashikhmin-Shirley
• Participating media
  Scattering, volumetric photon mapping, photon beams
• Higher dimensional effects
  Motion blur, depth of field
• Camera models
  Pinhole, Perspective, Orthographic
  
• Post processing
  HDR, tone mapping

Subject to refinement.

Literature

• Physically Based Rendering, Third Edition: From Theory To Implementation, M. Pharr and G. Humphreys, Homepage, ACM
  The main book of the lecture (referred to as PBRT).
  
  

• Course on Monte-Carlo Methods in Global Illumination, L. Szirmay-Kalos, Link
  A free course scriptum that gives a detailed explanation of the mathematical foundations of Global Illumination.

Lecture slides

• Unit 01 - Introduction, Radiometry (Thomas Auzinger)
• Unit 02 - The Rendering Equation and Ray Tracing (Károly Zsolnai-Fehér) - This lecture is now finalized for 2018.
• Unit 03 - Global Illumination and Path Tracing (Károly Zsolnai-Fehér) - This lecture is now finalized for 2018.
• Unit 04 - Part 01 - Spatial Acceleration Structures (Thomas Auzinger)
• Unit 04 - Part 02 - Tonemapping (Thomas Auzinger)
• Unit 05 - Part 01 - Participating Media (Thomas Auzinger)
• Unit 05 - Part 02 - Subsurface Scattering (Thomas Auzinger)
• Unit 06 - Smallpaint code walkthrough (Károly Zsolnai-Fehér) - This lecture is now finalized for 2018.
• Unit 07 - State of the art in Global Illumination (Károly Zsolnai-Fehér) - This lecture is now finalized for 2018.
• Bonus Unit - Blender and LuxRender (Károly Zsolnai-Fehér) - please note that LuxRender's Blender exporter has changed a bit since. Proceed with care! :)

Assignments

• Assignment 01 - Ray Tracing - Deadline: April 3rd, 23:59.
• Assignment 02 - Rendering Basics - Additional task: take at least 2 real-world photographs that showcase indirect illumination and caustics and include them in your submission. Deadline: May 29th, 23:59.
• Assignment 03 - Monte Carlo integration, smallpaint - Deadline: June 12th, 23:59.
• Assignment 04 - LuxRender scene competition - Deadline: officially June 30th, 23:59 - as discussed in the lecture, late submissions will get a deduction of this many points per day until July 5th, 23:59. Halfway report deadline: June 22th, 23:59. This is mandatory for everyone - details are available in the ppt file. As usual, I send back a personal evaluation for the final results, but not for the intermediate reports.

Example exam questions

• Explain how Photon Mapping works and draw an example run of the algorithm. What are the limitations of the algorithm? How do the advanced Photon Mapping variants address them?
• Classify the main light transport algorithms we studied during the course according to their consistency and bias (biased/unbiased, consistent/inconsistent and why).
• What is Next Event Estimation and how does it affect the convergence speed on indoors and outdoors scenes for a simple path tracer?