Methods for digitizing an object?s 3D shape and visual appearance have broad applications ranging from the digital arts to manufacturing, immersive virtual environments, entertainment, digital archives, and archeology. On the one hand, modern 3D scanning systems faithfully capture an object?s shape, but recover very little information about its material properties (often only a crude estimate of its diffuse albedo). On the other hand, techniques for measuring a surface?s spatially- and directionally-dependent appearance require a precise 3D model of the sample, usually obtained through a separate procedure. Although researchers have made significant progress on both fronts, shape and appearance acquisition have largely been studied separately. As a result, the few existing pipelines that allow synchronous capture suffer from cumbersome and error-prone registration steps, impractical calibration standards, and fail to take advantage of the potential benefits that a combined analysis would allow.
This research investigates new optical scanners and accompanying algorithms to provide a complete pipeline for automated and synchronous measurement of shape and surface appearance. These scanners are designed to reliably measure the 3D shape of real-world objects along with a complete model of the way incident light is reflected at their surfaces and (for translucent samples) scattered internally. This research also includes the development of algorithms that take into account both geometric and reflectance information during scan alignment and model recovery, along with view planning techniques that can identify optimal measurement sequences in this joint context. Academic and commercial areas that rely on 3D scanned objects (e.g., archaeology, engineering, medicine, and entertainment) will benefit from this research.
