1. Progressive Photon Mapping
최인창(Inchang Choi)
KAIST (Korea Advanced Institute of Science and Technology) 1

2. Intro: MC based methods
can simulate specular and diffuse material
Problems:
Caustics (LS+DE)
SDS paths (LSDSE)
Can simulate both specular and diffuse material
Problem1: caustic (definition) ->example
Problme2: SDS path -> example (swimming pool)
(sampling problem)

3. Intro: Photon Mapping Two pass algorithm Problem:
First pass: Photon Tracing
Second pass: Ray Tracing using the photon maps
Problem:
Scenes dominated by caustics
->We don’t have infinite memory
Ray tracing using photon mapps
First pass: photon tracing to make two photon maps
Second pass: ray tracing using photon map
Problem: if the scence is dominated by causitics illumination
(caustics usually are simulated by directily visualizing photon maps, and it requires too much memory) -> accuracy is regulated by memory available.

4. Intro: Progressive Photon Mapping
An extension of Photon Mapping
Include SDS paths with arbitrary accuracy without infinite memory
Multi-pass algorithm
First Pass: Ray Tracing
Subsequent Passes: Photon Tracing
A progressive photon mapping algorithm simulated global illumination including SDS paths with arbirtray accuracy without infinite memory.
Multipass alogrithm – 1. ray tracing 2. photon tracing

5. Photon Mapping

6. Photon Mapping: First Pass: Photon Tracing
Shoot photons from the light source
-using MC technique and Russian Roulette
-store photons in K-d tree
Position, incident direction, flux
Manage two photon maps
Caustic map
Global photon map
Caustic map photons
Global map photons
From John C. Hart’s ppt

7. Photon Mapping: Second Pass: Ray Tracing
Trace rays
Calculate illumination using two photon maps
DA = pr2
Use the nearest N photons to estimate L at point x
From John C. Hart’s ppt

8. Photon Mapping: Second Pass: Ray Tracing
Direct
Illumination
Diffuse Indirect
Illumination
Specular
Illumination
Caustic
Illumination
From Michael Kaiser and Christian Finger’s ppt

9. How can it be improved? 1. Make the number of photons very large
(lim n->∞)
Use an Iterative method
2. Reduce the radius r
(limt r-> 0)
Reduce the radius every iteration

10. Progressive Photon Mapping

11. Progressive Photon Mapping First Pass: Ray Tracing
Shoot a ray from eye to the scene
Trace the path until the first non-specular surface
Store the hit point if the surface has non- specular(diffuse) component in the BRDF

12. Progressive Photon Mapping First Pass: Ray Tracing
A Hit Point Structure
These are updated each subsequent passes

13. Progressive Photon Mapping Subsequent Pass: Photon Tracing
In each Pass
Trace a given number of photons into the scene

14. Progressive Photon Mapping Subsequent Pass: Photon Tracing
After each Pass
Loop all hit points
:Find the photons within the radius
:refine the estimate of the illumination
(Reduce R, increase N, update τ)

15. Progressive Photon Mapping Radius Reduction

16. Progressive Photon Mapping Flux Correction

17. Progressive Photon Mapping Radiance Evaluation

18. A Video Result

19. Result Comparison

20. Thank you for listening
Any Questions?