A new method of adaptable rendering for interaction in Virtual Environment(VE) through different visual acuity equations is proposed. An acuity factor equation of luminance vision is first given. Secondly, five equati...A new method of adaptable rendering for interaction in Virtual Environment(VE) through different visual acuity equations is proposed. An acuity factor equation of luminance vision is first given. Secondly, five equations which calculate the visual acuity through visual acuity factors are presented, and adaptive rendering strategy based on different visual acuity equations is given. The VE system may select one of them on the basis of the host’s load, hereby select LOD for each model which would be rendered. A coarser LOD is selected where the visual acuity is lower, and a better LOD is used where it is higher. This method is tested through experiments and the experimental results show that it is effective.展开更多
Gradient-domain rendering estimates finite difference gradients of image intensities and reconstructs the final result by solving a screened Poisson problem,which shows improvements over merely sampling pixel intensit...Gradient-domain rendering estimates finite difference gradients of image intensities and reconstructs the final result by solving a screened Poisson problem,which shows improvements over merely sampling pixel intensities.Adaptive sampling is another orthogonal research area that focuses on distributing samples adaptively in the primal domain.However,adaptive sampling in the gradient domain with low sampling budget has been less explored.Our idea is based on the observation that signals in the gradient domain are sparse,which provides more flexibility for adaptive sampling.We propose a deep-learning-based end-to-end sampling and reconstruction framework in gradient-domain rendering,enabling adaptive sampling gradient and the primal maps simultaneously.We conducted extensive experiments for evaluation and showed that our method produces better reconstruction quality than other methods in the test dataset.展开更多
文摘A new method of adaptable rendering for interaction in Virtual Environment(VE) through different visual acuity equations is proposed. An acuity factor equation of luminance vision is first given. Secondly, five equations which calculate the visual acuity through visual acuity factors are presented, and adaptive rendering strategy based on different visual acuity equations is given. The VE system may select one of them on the basis of the host’s load, hereby select LOD for each model which would be rendered. A coarser LOD is selected where the visual acuity is lower, and a better LOD is used where it is higher. This method is tested through experiments and the experimental results show that it is effective.
基金supported by the Key R&D Program of Zhejiang Province(No.2023C01039).
文摘Gradient-domain rendering estimates finite difference gradients of image intensities and reconstructs the final result by solving a screened Poisson problem,which shows improvements over merely sampling pixel intensities.Adaptive sampling is another orthogonal research area that focuses on distributing samples adaptively in the primal domain.However,adaptive sampling in the gradient domain with low sampling budget has been less explored.Our idea is based on the observation that signals in the gradient domain are sparse,which provides more flexibility for adaptive sampling.We propose a deep-learning-based end-to-end sampling and reconstruction framework in gradient-domain rendering,enabling adaptive sampling gradient and the primal maps simultaneously.We conducted extensive experiments for evaluation and showed that our method produces better reconstruction quality than other methods in the test dataset.
