caa a22 4500 605540179 CHVBK 20210128100910.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s00371-013-0908-z doi (NATIONALLICENCE)springer-10.1007/s00371-013-0908-z Robust and efficient adaptive direct lighting estimation [Elektronische Daten] [Yu-Chi Lai, Hsuan-Ting Chou, Kuo-Wei Chen, Shaohua Fan] Hemispherical integrals are important for the estimation of direct lighting which has a major impact on the results of global illumination. This work proposes the population Monte Carlo hemispherical integral (PMC-HI) sampler to improve the efficiency of direct lighting estimation. The sampler is unbiased and derived from the population Monte Carlo framework which works on a population of samples and learns to be a better sampling function over iterations. Information found in one iteration can be used to guide subsequent iterations by distributing more samples to important sampling techniques to focus more efforts on the sampling sub-domains which have larger contributions to the hemispherical integrals. In addition, a cone sampling strategy is also proposed to enhance the success rate when complex occlusions exist. The images rendered with PMC-HI are compared against those rendered with multiple importance sampling (Veach and Guibas In: SIGGRAPH '95, pp 419-428, 1995), adaptive light sample distributions (Donikian et al. IEEE Trans Vis Comput Graph 12(3):353-364, 2006), and multidimensional hemispherical adaptive sampling (Hachisuka et al. ACM Trans Graph 27(3):33:1-33:10, 2008). Our PMC-HI sampler can improve rendering efficiency. Springer-Verlag Berlin Heidelberg, 2014 Ray-tracing nationallicence PMC nationallicence Monte Carlo nationallicence Global illumination nationallicence Lai Yu-Chi National Taiwan University of Science and Technology, Taipei, Taiwan, ROC aut Chou Hsuan-Ting National Taiwan University of Science and Technology, Taipei, Taiwan, ROC aut Chen Kuo-Wei National Taiwan University of Science and Technology, Taipei, Taiwan, ROC aut Fan Shaohua China and NYU Courant Institute of Mathematical Sciences, Suzhou University, Suzhou, China aut The Visual Computer Springer Berlin Heidelberg 31/1(2015-01-01), 83-91 0178-2789 31:1<83 2015 31 371 https://doi.org/10.1007/s00371-013-0908-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-013-0908-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lai Yu-Chi National Taiwan University of Science and Technology, Taipei, Taiwan, ROC aut NATIONALLICENCE 700 1- Chou Hsuan-Ting National Taiwan University of Science and Technology, Taipei, Taiwan, ROC aut NATIONALLICENCE 700 1- Chen Kuo-Wei National Taiwan University of Science and Technology, Taipei, Taiwan, ROC aut NATIONALLICENCE 700 1- Fan Shaohua China and NYU Courant Institute of Mathematical Sciences, Suzhou University, Suzhou, China aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/1(2015-01-01), 83-91 0178-2789 31:1<83 2015 31 371