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.
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Item Seeing The Divine Through Darkness: Illuminations of Christ Healing the Blind Man, C. 1200-1400(2021) Prescott, Hannah; Gill, Meredith J.; Art History and Archaeology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In the thirteenth and fourteenth centuries, the image of Christ healing the blind man began to appear alongside psalmic text in western European psalters and books of hours. In this thesis, I elucidate the devotional implications of the miracle of the blind man, foregrounding illuminated examples—located in the Rutland Psalter, Saint Elizabeth Psalter, Taymouth Hours, and Psalter-Hours of Yolande de Soissons—within the context of period discourse concerning the corporeal and spiritual nature of the eye. My discussion first considers how lay viewers perceived the miraculous restoration of sight as a reflection of the process of divine illumination and contemplative ascent. I then elaborate upon the relationship between blindness, the sacrament of Baptism, and medieval Passion Plays, demonstrating how the blind man’s place within the overall decorative program of each manuscript underlines the soteriological significance of this miracle and its role as a necessary precursor to the Resurrection.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 Shadow detection in videos acquired by stationary and moving cameras(2005-12-09) Trias, Antonio; Chellappa, Rama; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Shadow Detection has become a key issue in object detection, tracking and recognition problems. Object appearances might be completely changed by the effects of shading and shadows. Finding good algorithms for shadow detection and reducing shading effects in order to segment objects from video sequences, will enhance the performance of our detection, tracking and recognition algorithms. In this thesis, we present data, physics and model-driven approaches for detecting shadows and correcting shading effects. The effectiveness of these algorithms in video sequences acquired by stationary surveillance cameras and airborne platforms is illustrated.