Theses and Dissertations from UMD
Permanent URI for this communityhttp://hdl.handle.net/1903/2
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
Browse
2 results
Search Results
Item Dense Wide-Baseline Stereo with Varying Illumination and its Application to Face Recognition(2012) Castillo, Carlos Domingo; Jacobs, David W; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We study the problem of dense wide baseline stereo with varying illumination. We are motivated by the problem of face recognition across pose. Stereo matching allows us to compare face images based on physically valid, dense correspondences. We show that the stereo matching cost provides a very robust measure of the similarity of faces that is insensitive to pose variations. We build on the observation that most illumination insensitive local comparisons require the use of relatively large windows. The size of these windows is affected by foreshortening. If we do not account for this effect, we incur misalignments that are systematic and significant and are exacerbated by wide baseline conditions. We present a general formulation of dense wide baseline stereo with varying illumination and provide two methods to solve them. The first method is based on dynamic programming (DP) and fully accounts for the effect of slant. The second method is based on graph cuts (GC) and fully accounts for the effect of both slant and tilt. The GC method finds a global solution using the unary function from the general formulation and a novel smoothness term that encodes surface orientation. Our experiments show that DP dense wide baseline stereo achieves superior performance compared to existing methods in face recognition across pose. The experiments with the GC method show that accounting for both slant and tilt can improve performance in situations with wide baselines and lighting variation. Our formulation can be applied to other more sophisticated window based image comparison methods for stereo.Item Deterministic Annealing for Correspondence, Pose, and Recognition(2006-04-27) David, Philip John; DeMenthon, Daniel; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The problem of determining the pose - the position and orientation - of an object given a model and an image of that object is a fundamental problem in computer vision. Applications include object recognition, object tracking, site inspection and updating, and autonomous navigation when scene models are available. The pose of an object is readily determined given a few correspondences between features in the image and features in the model. Conversely, corresponding model and image features can easily be determined if the pose of the object is known. However, when neither the pose nor the correspondences are known, the problem of determining either is difficult due to the fact that a small change in an object's pose can result in a large change in its appearance. Most existing techniques approach this as a combinatorial optimization problem in which the space of model-to-image feature correspondence is searched in order to find object poses that are supported by large numbers of image features. These approaches, however, are only practical when the level of clutter and occlusion in the image is small, which is often not the case in real-world environments. This dissertation presents new algorithms that simultaneously determine the pose and feature correspondences of 2D and 3D objects from images containing large amounts of clutter and occlusion. Objects are modeled as sets of 2D or 3D points or line segments, and image features consist of either points or line segments. In each of the algorithms presented, deterministic annealing is used to convert a discrete combinatorial optimization problem into a continuous one that is indexed by a control parameter. This has two advantages. First, it allows solutions to the simpler continuous problem to slowly transform into a solution to the discrete problem. Secondly, many local minima are avoided by minimizing an objective function that is highly smoothed during the early phases of the optimization but which gradually transforms into the original objective function and constraints at the end of the optimization. These algorithms perform well in experiments involving highly cluttered synthetic and real imagery.