Alex Golovinskiy will present his preFPO on Wednesday March 4 at 11:30 AM in Room 401 (note room). The members of his committee are: Tom Funkhouser, advisor; Adam Finkelstein and Szymon Rusinkiewicz, readers; David Dobkin and Rob Schapire, nonreaders. Everyone is invited to attend his talk. His abstract follows below. ------------------------ Algorithms for analyzing the texture, symmetry, and part structure of 3D surface models Abstract: While much of computer graphics research has focused on low-level primitives, many computer graphics applications require reasoning about higher level structures. In response to this need, research has emerged to find and take advantage of higher level structures such as textural properties of geometry, symmetries, and functional parts. We advance this line of research in several directions. First, we present a method for analyzing and modifying detailed facial geometry. We introduce a statistical technique for the analysis and synthesis of small three-dimensional facial features, such as wrinkles and pores. As an initial step, our method separates the skin surface details from a smooth base mesh. Then, we analyze the resulting displacement maps and synthesize new geometry using tools from texture synthesis research. We demonstrate this method for analysis of changes of facial texture with respect to age and gender, detail-preserving interpolation between high-resolution face models, adding detail to low-resolution face models, and adjusting the apparent age of face models. Second, we present a framework for symmetry-aware mesh processing. Although perfect, partial, and approximate symmetries are pervasive in real-world geometry, current geometry processing algorithms ignore them. We present a framework in which, given a set of symmetries, we (i) warp the geometry to be symmetric, and (ii) re-mesh a model to have symmetric triangulation. We show how to use this framework to create algorithms that respect the symmetries of a model, and demonstrate applications for modeling, beautification, and simplification of nearly symmetric surfaces. Third, we present several investigations into segmenting meshes into parts. We present a hierarchical aggregation algorithm for mesh segmentation. We then expand this algorithm to consistently segment a set of meshes. We also show how to modify mesh segmentation algorithms to produce a soft, randomized version of segmentation. Finally, we present a framework for finding and recognizing objects in outdoor point cloud scans. We present methods for locating potential objects, segmenting them, and classifying them. We quantitatively evaluate these models on a part of an Ottawa scan.