Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 8

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

Quality Metric for Shadow Rendering

DOI: http://dx.doi.org/10.15439/2016F494

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 791796 ()

Full text

Abstract. Shadow rendering is one of the most important aspects of rendering 3D environments, yet, the problem is far from trivial. A number of shadow rendering algorithms exist, with various degrees of rendering quality, fidelity and performance. Additionally, many of such algorithms offer high degrees of flexibility when it comes to fine tuning. This paper proposes a new method of measurement of quality of shadows produced by rendering algorithms, which method can be used for automation of algorithm choice and fine-tuning of such algorithms to specific data sets and use cases.

References

  1. P. Boulenguez, B. Airieau, M.-C. Larabi, D. Meneveaux, “Towards a perceptual quality metric for computer-generated images,” in Proc. SPIE 8293, Image Quality and System Performance IX, Burlingame, CA 2012, http://dx.doi.org/10.1117/12.908067.
  2. L. Williams, "Casting curved shadows on curved surfaces", Proc. of the 5th annual conference on Computer graphics and interactive techniques - SIGGRAPH '78, 1978.
  3. R. Herzog, M. Čadík, T. O. Aydčin, K. I. Kim. K. Myszkowski, H. P. Seidel, H. (2012). NoRM: No-Reference Image Quality Metric for Realistic Image Synthesis. Computer Graphics Forum, 31(2pt3), pp. 545-554.
  4. R. Piórkowski, "Automatic Detection of Shadow Acne and Peter Panning Artefacts in Computer Games." in Central European Seminar on Computer Graphics for students 2015, Smolenice, Slovakia, pp 117-123.
  5. Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, "Image quality assessment: from error visibility to structural similarity," in IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600-612, April 2004.
  6. Z. Wang, E. P. Simoncelli, A. C. Bovik, "Multiscale structural similarity for image quality assessment," Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on, 2003, pp. 1398-1402 Vol.2. http://dx.doi.org/10.1109/ACSSC.2003.1292216
  7. L. S. Davis, "A survey of edge detection techniques", Computer Graphics and Image Processing, vol 4, no. 3, pp 248-260, 1975
  8. H.-C. Liao, “Shadow mapping for omni-directional light using tetrahedron mapping”, in GPU Pro: Advanced Rendering Techniques, Boca Raton, CRC Press, 2010, pp. 455–475.