Virtual-Point-Light Sampling Algorithm Based on Indirect Illumination Clustering of Visible Scene Region

doi:10.16182/j.issn1004731x.joss.18-VR0742

Abstract

Abstract: Focusing on the accuracy of indirect illumination calculation, an improved view-sensitive virtual point light (VPL) sampling method is proposed. The visible shading points are clustered according to the positions and normal vectors. The product of the contribution of VPLs on the representative visible shading points and the number of VPLs belonging to the same class is calculated, and the sum of the products is treated as the estimation of the indirect illumination which constructs the cumulative distribution function (CDF). On the basis of the CDF, the VPLs of calculating the indirect illumination on every visible shading point are selected. Experiment results show that the proposed algorithm can achieve better indirect lighting effect with fewer VPLs, and improve the accuracy of indirect illumination calculation.

Key words: virtual point light, visible shading point clustering, indirect illumination, importance sampling

CLC Number:

TP314

Chen Sheng, Chen Chunyi*, Xing Qiwei, Yang Chaozhi. Virtual-Point-Light Sampling Algorithm Based on Indirect Illumination Clustering of Visible Scene Region[J]. Journal of System Simulation, 2020, 32(6): 1085-1093.

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