Visual importance-based adaptive photon tracing

Abstract

This paper proposes an adaptive photon tracing approach based on a novel importance function, which combines visual importance and photon path visibility. The generation of photon path is guided by sampling this function to trace more photons to visible and more contributive regions. As a first step, a hierarchy of visual importance maps is constructed. Next, photon paths are produced using a new hybrid mutation strategy, which consists of large mutation and small mutation. The mutation parameter used in small mutation is automatically adjusted using the adaptive Markov chain sampling method. Meanwhile, to find a suitable initial parameter, a mutation parameter initialization method is developed. Experiments show that, compared with previous methods, this approach yields results with better visual quality and smaller numerical error.

Neural Relightable Participating Media Rendering

“…Recent approaches [8,9] decompose materials and lighting by assuming an opaque surface at each point, but this does not apply to participating media. After training, density and materials can be extracted [41] to render new views using Monte Carlo methods [42,43,44]. Instead, our method models participating media as a field of particles that scatter and absorb light, which are in accordance with its nature.…”

Editorial

“…Five papers on rendering and graphics hardware are in this special issue: the paper by Zheng and Zheng [24] is about photon tracing; the paper by Vanhoey et al [25] focuses on the mesh simplification using radiance; Adhikarla et al [26] describe a method to increase the quality of visual perception on light field display; Rodríguez-Cerro et al [27] present a technique for texture advection. The last paper by Kim and Kim [28] presents a method to improve the performance of graphics processor units.…”