Appearance Modeling via Proxy-to-Image Alignment

Abstract

Endowing 3D objects with realistic surface appearance is a challenging and time-demanding task, as real-world surfaces typically exhibit a plethora of spatially variant geometric and photometric detail. Not surprisingly, computer artists commonly use images of real-world objects as an inspiration and a reference for their digital creations. However, despite two decades of research on image-based modeling, there are still no tools available for automatically extracting the detailed appearance (microgeometry and texture) of a 3D surface from a single image. In this article, we present a novel user-assisted approach for quickly and easily extracting a nonparametric appearance model from a single photograph of a reference object. The extraction process requires a user-provided proxy, whose geometry roughly approximates that of the object in the image. Since the proxy is just a rough approximation, it is necessary to align and deform it so as to match the reference object. The main contribution of this work is a novel technique to perform such an alignment, which enables accurate joint recovery of geometric detail and reflectance. The correlations between the recovered geometry at various scales and the spatially varying reflectance constitute a nonparametric appearance model. Once extracted, the appearance model may then be applied to various 3D shapes, whose large-scale geometry may differ considerably from that of the original reference object. Thus, our approach makes it possible to construct an appearance library, allowing users to easily enrich detail-less 3D shapes with realistic geometric detail and surface texture.