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Lectures

Week 1: Introduction to python and Numpy Week 2: Lightprobe code   Midpoint rules Week 3: midpoint rule for R1 (with Monte Carlo) Week 4: Visualization of point distributions on H^2 Week 5: Notes on curse of dimensionality Week 6: Monte Carlo code for measurements Week 7: Ray tracer (V1) Week 8: Ray tracer (V2) Week 9: Ray tracer (V3) Week 10: Task   Ray tracer (V4) Week 10: Task   Ray tracer (V5) Week 11: Sobol points   Ray tracer (V6) Week 12: Final tasks Week 12: gHalton library

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Readings

Week 1: H. W. Jensen and T. Akenine-Möller, The Race for Real-Time Photorealism, Am. Sci., vol. 98, no. 2, pp. 132–139, 2010. Week 2: P. Hanrahan, Rendering Concepts, in Radiosity and Realistic Image Synthesis, M. F. Cohen and J. Wallace, Eds. San Diego, CA, USA: Academic Press Professional, Inc., 1993.

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Resources

• Anaconda python environment (please use Python 3.7 version)

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Literature

• M. Pharr and G. Humphreys, Physically Based Rendering: From Theory to Implementation, Second. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2010
• H. W. Jensen, Realistic Image Synthesis using Photon Mapping. Natick, MA, USA: A. K. Peters, Ltd., 2001
• P. Dutré, K. Bala, and P. Bekaert, Advanced Global Illumination. Natick, MA, USA: A. K. Peters, Ltd., 2006
• J. Dick and F. Pillichshammer, Digital Nets and Sequences: Discrepancy Theory and Quasi-Monte Carlo Integration. Cambridge University Press, 2010.
• P. Hanrahan, E. Veach, and D. Zorin, Mathematical Models for Computer Graphics Lecture Notes, 1997, Lectures 6-8.