Progressive photon mapping for daylight redirecting components

AbstractDaylight redirecting components (DRCs) are characterised by complex transmissive and reflective behaviour that is difficult to predict accurately largely due to their highly directional scattering, and the caustics this produces. This paper examines the application of progressive photon mapping as a state of the art forward raytracing technique to efficiently simulate the behaviour of such DRCs, and how this approach can support architects in assessing their performance.Progressive photon mapping is an iterative variant of static photon mapping that effects noise reduction through accumulation of results, as well as a reduction in bias inherent to all density estimation methods by reducing the associated bandwidth at a predetermined rate. This not only results in simplified parametrisation for the user, but also provides a preview of the progressively refined simulation, thus making the tool accessible to non-experts as well.We demonstrate the effectiveness of this technique with an implementation based on the Radiancephoton mapping extension and a case study involving retroreflecting prismatic blinds as a representative DRC

Bias compensation for photon maps

Density estimation techniques such as the photon map method rely on a particle transport simulation to reconstruct indirect illumination, which is proportional to the particle density. In the photon map framework, particles are usually located using nearest-neighbour methods due to their generality. However these methods have an inherent tradeoff between local bias and noise in the reconstructed illumination, which depends on the density estimate bandwidth. This paper presents a bias compensating operator for nearest-neighbour density estimation which adapts the bandwidth according to the estimated bias in the reconstructed illumination

Grand Challenges: Material Models in the Automotive Industry

Material reflectance definitions are core to high fidelity visual simulation of objects within a compelling 3D scene. In the automotive industry these are used across the entire business process: from conceptualisation of a new product range, through to the final sale. However, current state-of-the-art of material representations leave much to be desired for fast and practical deployment in the industry. Even after decades of research and development, there are no interoperable standards for material models to facilitate exchange between applications. A large discrepancy also exists between the quality of material models used (and indeed the quality at which they can be displayed) across the spectrum of use-cases within the industry. Focussing on the needs of the Automotive Industry, in this position paper, we summarise the main issues that limit the effective use of material models. Furthermore, we outline specific solutions we believe could be investigated in order to address this problem. This paper is the result of a review conducted in conjunction with several key players in the automotive field