In this dissertation we discuss a variety of techniques that advance the state of the art in the field of 3D shape acquisition from real world objects. The research was done in collaboration with Szymon Rusinkiewicz, James Davis, Ravi Ramammorthi, and Tim Weyrich. Our first contribution is a new framework for the classification of stereo triangulation algorithms. We classify methods according to the dimensions along which observations by both cameras are matched against each other. Different algorithms consider information that extends in space, in time, or simultaneously in both dimensions. Based on this framework, we design a novel algorithm for the triangulation of dynamic objects, as well as a new stereo setup based on unstructured active lighting. We then present a novel sub-pixel precision refinement algorithm for stereo matches. We treat both cameras symmetrically, instead of assuming one camera to provide a reference image to be matched against. By refining match coordinates simultaneously on both cameras, we avoid a source of bias that can otherwise manifest itself as coherent noise in the reconstructions. We also provide an efficient algorithm for combining position and orientation measurements into an optimal surface. Since position and orientation measurements are obtained from independent sources, each contains errors with distinct frequency characteristics. By optimizing a surface to conform to the most precise frequency components from each source, we can produce reconstructions that are substantially more precise than the original measurements. Finally, we present a strategy for the acquisition of the 3D shape of shiny objects. Standard triangulation strategies that rely on captured appearances fail due to the view dependent nature of the images of such objects. We present a matching cost function based on surface normal consistency that can be used with standard dense stereo matching algorithms, and discuss the ambiguities that can arise.

@phdthesis{:2007:AI3,
   author = "Diego Nehab",
   title = "Advances in {3D} Shape Acquisition",
   school = "Princeton University",
   year = "2007",
   month = sep
}