Real-time human vision rendering using blur distribution function

We propose a real-time rendering method which is based on the Blur Distribution Function(BDF) of human eye in order to achieve vision-realistic effect. In real-time rendering, a thin lens camera model is commonly adopted to simulate the effect of Depth of Field(DoF). Thin lens model is efficient to calculate but lacks vision-realistic effect. We consider the simulation of human vision an improvement in virtual reality. In this paper, we analysis and model the BDF of human eye. The BDF is calculated quickly by neural network to simulate blur size of each pixel. Based on a schematic eye model, which provides accurate optical properties of human eye, our method shows DoF effect simulating human vision. Evaluation results indicate that the rendering effect of our method conforms to human vision and extra computation cost is acceptable.

Publication: Tang N, Xiao S J. Real-time human vision rendering using blur distribution function[C]//Proceedings of the 14th ACM SIGGRAPH International Conference on Virtual Reality Continuum and its Applications in Industry. 2015: 39-42.

Preprint PDF: Real-time human vision rendering using blur distribution function.pdf

Citation:

@inproceedings{tang2015real,
title={Real-time human vision rendering using blur distribution function},
author={Tang, Ning and Xiao, ShuangJiu},
booktitle={Proceedings of the 14th ACM SIGGRAPH International Conference on Virtual Reality Continuum and its Applications in Industry},
pages={39–42},
year={2015}
}