Sparkle Vision: Seeing the World through Random Specular Microfacets

TL;DR

This paper introduces a novel imaging system and algorithms to infer environmental lighting from a single image of an object covered with random specular microfacets, enabling accurate lighting reconstruction.

Contribution

It presents a new approach to model and photograph specular microfacet surfaces, along with calibration and inference algorithms for lighting estimation.

Findings

Successful modeling of microfacet reflectors as randomized lighting mappings

Effective calibration and inference algorithms demonstrated

Experimental validation confirms model accuracy and pipeline robustness

Abstract

In this paper, we study the problem of reproducing the world lighting from a single image of an object covered with random specular microfacets on the surface. We show that such reflectors can be interpreted as a randomized mapping from the lighting to the image. Such specular objects have very different optical properties from both diffuse surfaces and smooth specular objects like metals, so we design special imaging system to robustly and effectively photograph them. We present simple yet reliable algorithms to calibrate the proposed system and do the inference. We conduct experiments to verify the correctness of our model assumptions and prove the effectiveness of our pipeline.