Theses and Dissertations from UMD
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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 Dynamic EM Ray Tracing for Complex Outdoor and Indoor Environments with Multiple Receivers(2024) Wang, Ruichen; Manocha, Dinesh; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Ray tracing models for visual, aural, and EM simulations have advanced, gaining traction in dynamic applications such as 5G, autonomous vehicles, and traffic systems. Dynamic ray tracing, modeling EM wave paths and their interactions with moving objects, leads to many challenges in complex urban areas due to environmental variability, data scarcity, and computational needs. In response to these challenges, we've developed new methods that use a dynamic coherence-based approach for ray tracing simulations across EM bands. Our approach is designed to enhance efficiency by improving the recomputation of bounding volume hierarchy (BVH) and by caching propagation paths. With our formulation, we've observed a reduction in computation time by about 30%, all while maintaining a level of accuracy comparable to that of other simulators. Building on our dynamic approach, we've made further refinements to our algorithm to better model channel coherence, spatial consistency, and the Doppler effect. Our EM ray tracing algorithm can incrementally improve the accuracy of predictions relating to the movement and positioning of dynamic objects in the simulation. We've also integrated the Uniform Geometrical Theory of Diffraction (UTD) with our ray tracing algorithm. Our enhancement is designed to allow for more accurate simulations of diffraction around smooth surfaces, especially in complex indoor settings, where accurate prediction is important. Taking another step forward, we've combined machine learning (ML) techniques with our dynamic ray tracing framework. Leveraging a modified conditional Generative Adversarial Network (cGAN) that incorporates encoded geometry and transmitter location, we demonstrate better efficiency and accuracy of simulations in various indoor environments with 5X speedup. Our method aims to not only improve the prediction of received power in complex layouts and reduce simulation times but also to lay a groundwork for future developments in EM simulation technologies, potentially including real-time applications in 6G networks. We evaluate the performance of our methods in various environments to highlight the advantages. In dynamic urban scenes, we demonstrate our algorithm’s scalability to vast areas and multiple receivers with maintained accuracy and efficiency compared to prior methods; for complex geometries and indoor environments, we compare the accuracy with analytical solutions as well as existing EM ray tracing systems.Item Speech Segregation and Representation in the Ferret Auditory and Frontal Cortices(2022) Joshi, Neha Hemant; Shamma, Shihab; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The problem of separating overlapping streams of sound, and selectively attending to a sound of interest is ubiquitous in humans and animals alike as a means for survival and communication. This problem, known as the cocktail party problem, is the focus of this thesis, where we explore the neural correlates of two-speaker segregation in the auditory and frontal cortex, using the ferret as an animal model. While speech segregation has been studied extensively in humans using various non-invasive imaging as well as some restricted invasive techniques, these do not provide a way to obtain neural data at the single-unit level. In animal models, streaming studies have been limited to simple stimuli like tone streams, or sound in noise. In this thesis, we extend this work to understand how complex auditory stimuli such as human speech is encoded at the single-unit and population level in both the auditory cortex, as well as the frontal cortex of the ferret. In the first part of the thesis, we explore current literature in auditory streaming and design a behavioral task using the ferret as an animal model to perform stream segregation. We train ferrets to selectively listen to one speaker over another, and perform a task to indicate detection of the attended speaker. We show the validity of this behavioral task, and the reliability with which the animal performs this task of two speaker stream segregation. In the second part, we collect neurophysiological data which is post-processed to obtain data from single units in both the auditory cortex (the primary auditory cortex, and the secondary region which includes the dorsal posterior ectosylvian gyrus) as well as the dorsolateral aspect of the frontal cortex of the ferret. We analyse the data and present findings of how the auditory and frontal cortices encode the information required to reliably segregate the speaker of relevance from the mixture of two speakers, and the insights provided into stream segregation mechanisms and the cocktail party solved by animals using neural decoding approaches. We finally demonstrate that stream segregation has already begun at the level of the primary auditory cortex. In agreement with previous attention-modulated neural studies in the auditory cortex, we show that this stream segregation is more pronounced in the secondary cortex, where we see clear enhancement of the attended speaker, and suppression of the unattended speaker. We explore the contribution of various areas within the primary and secondary regions, and how it relates to speaker selectivity of individual neuronal units. We also study the neural encoding of top-down attention modulation in the ferret frontal cortex. Finally, we discuss the conclusions from these results in the broader context of their relevance to the field, and what future directions it may hold for the field.Item Real-time Audio Reverberation for Virtual Room Acoustics(2020) Shen, Justin M; Duraiswami, Ramani; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)For virtual and augmented reality applications, it is desirable to render audio sources in the space the user is in, in real-time without sacrificing the perceptual quality of the sound. One aspect of the rendering that is perceptually important for a listener is the late-reverberation, or "echo", of the sound within a room environment. A popular method of generating a plausible late reverberation in real-time is the use of Feedback Delay Network (FDN). However, its use has the drawback that it first has to be tuned (usually manually) for a particular room before the late-reverberation generated becomes perceptually accurate. In this thesis, we propose a data-driven approach to automatically generate a pre-tuned FDN for any given room described by a set of room parameters. When combined with existing method for rendering the direct path and early reflections of a sound source, we demonstrate the feasibility of being able to render audio source in real-time for interactive applications.Item Constant Amplitude Zero Autocorrelation Sequences and Single Pixel Camera Imaging(2018) Magsino, Mark; Benedetto, John J; Mathematics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The primary focus is on Constant Amplitude Zero Autocorrelation sequences, or CAZAC sequences for short. We provide both an exposition and some new results relating to CAZAC sequences. We then apply them to Gabor frames and prove a condition for checking when Gabor systems generated by a CAZAC sequence are tight frames. We also construct multiple examples using this condition. Finally, we explore natural generalizations of CAZAC sequences to the torus and the real line and provide examples highlighting the differences between the generalizations. In the last section, we highlight some work done in image processing. In particular, we present results in single-pixel camera imaging and the demosaicing problem in image processing.Item Edge-Based Automated Facial Blemish Removal(2013) NessAiver, Avisha; Chellappa, Rama; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis presents an end-to-end approach for taking a an image of a face and seamlessly isolating and filling in any blemishes contained therein. This consists of detecting the face within a larger image, building an accurate mask of the facial features so as not to mistake them as blemishes, detecting the blemishes themselves and painting over them with accurate skin tones. We devote the first part of the thesis to detailing our algorithm for extracting facial features. This is done by first improving the image through histogram equal- ization and illumination compensation followed by finding the features themselves from a computed edge map. Geometric knowledge of general feature positioning and blemish shapes is used to determine which edge clusters belong to correspond- ing facial features. Color and reflectance thresholding is then used to build a skin map. In the second part of the thesis we identify the blemishes themselves. A Lapla- cian of Gaussian blob detector is used to identify potential candidates. Thresholding and dilating operations are then performed to trim this candidate list down followed by the use of various morphological properties to reject regions likely to not be blem- ishes. Finally, in the third part, we examine four possible techniques for inpainting blemish regions once found. We settle on using a technique that fills in pixels based on finding a patch in the nearby image region with the most similar surrounding texture to the target pixel. Priority in the pixel fill-order is given to strong edges and contours.Item Digital Multimedia Forensics and Anti-Forensics(2012) Stamm, Matthew Christopher; Liu, K. J. Ray; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As the use of digital multimedia content such as images and video has increased, so has the means and the incentive to create digital forgeries. Presently, powerful editing software allows forgers to create perceptually convincing digital forgeries. Accordingly, there is a great need for techniques capable of authenticating digital multimedia content. In response to this, researchers have begun developing digital forensic techniques capable of identifying digital forgeries. These forensic techniques operate by detecting imperceptible traces left by editing operations in digital multimedia content. In this dissertation, we propose several new digital forensic techniques to detect evidence of editing in digital multimedia content. We begin by identifying the fingerprints left by pixel value mappings and show how these can be used to detect the use of contrast enhancement in images. We use these fingerprints to perform a number of additional forensic tasks such as identifying cut-and-paste forgeries, detecting the addition of noise to previously JPEG compressed images, and estimating the contrast enhancement mapping used to alter an image. Additionally, we consider the problem of multimedia security from the forger's point of view. We demonstrate that an intelligent forger can design anti-forensic operations to hide editing fingerprints and fool forensic techniques. We propose an anti-forensic technique to remove compression fingerprints from digital images and show that this technique can be used to fool several state-of-the-art forensic algorithms. We examine the problem of detecting frame deletion in digital video and develop both a technique to detect frame deletion and an anti-forensic technique to hide frame deletion fingerprints. We show that this anti-forensic operation leaves behind fingerprints of its own and propose a technique to detect the use of frame deletion anti-forensics. The ability of a forensic investigator to detect both editing and the use of anti-forensics results in a dynamic interplay between the forger and forensic investigator. We use develop a game theoretic framework to analyze this interplay and identify the set of actions that each party will rationally choose. Additionally, we show that anti-forensics can be used protect against reverse engineering. To demonstrate this, we propose an anti-forensic module that can be integrated into digital cameras to protect color interpolation methods.Item Multimedia Social Networks: Game Theoretic Modeling and Equilibrium Analysis(2011) Chen, Yan; Liu, K. J. Ray; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Multimedia content sharing and distribution over multimedia social networks is more popular now than ever before: we download music from Napster, share our images on Flickr, view user-created video on YouTube, and watch peer-to-peer television using Coolstreaming, PPLive and PPStream. Within these multimedia social networks, users share, exchange, and compete for scarce resources such as multimedia data and bandwidth, and thus influence each other's decision and performance. Therefore, to provide fundamental guidelines for the better system design, it is important to analyze the users' behaviors and interactions in a multimedia social network, i.e., how users interact with and respond to each other. Game theory is a mathematical tool that analyzes the strategic interactions among multiple decision makers. It is ideal and essential for studying, analyzing, and modeling the users' behaviors and interactions in social networking. In this thesis, game theory will be used to model users' behaviors in social networks and analyze the corresponding equilibria. Specifically, in this thesis, we first illustrate how to use game theory to analyze and model users' behaviors in multimedia social networks by discussing the following three different scenarios. In the first scenario, we consider a non-cooperative multimedia social network where users in the social network compete for the same resource. We use multiuser rate allocation social network as an example for this scenario. In the second scenario, we consider a cooperative multimedia social network where users in the social network cooperate with each other to obtain the content. We use cooperative peer-to-peer streaming social network as an example for this scenario. In the third scenario, we consider how to use the indirect reciprocity game to stimulate cooperation among users. We use the packet forwarding social network as an example. Moreover, the concept of ``multimedia social networks" can be applied into the field of signal and image processing. If each pixel/sample is treated as a user, then the whole image/signal can be regarded as a multimedia social network. From such a perspective, we introduce a new paradigm for signal and image processing, and develop generalized and unified frameworks for classical signal and image problems. In this thesis, we use image denoising and image interpolation as examples to illustrate how to use game theory to re-formulate the classical signal and image processing problems.Item Securing Multi-Layer Communications: A Signal Processing Approach(2006-07-17) Mao, Yinian; Wu, Min; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Security is becoming a major concern in this information era. The development in wireless communications, networking technology, personal computing devices, and software engineering has led to numerous emerging applications whose security requirements are beyond the framework of conventional cryptography. The primary motivation of this dissertation research is to develop new approaches to the security problems in secure communication systems, without unduly increasing the complexity and cost of the entire system. Signal processing techniques have been widely applied in communication systems. In this dissertation, we investigate the potential, the mechanism, and the performance of incorporating signal processing techniques into various layers along the chain of secure information processing. For example, for application-layer data confidentiality, we have proposed atomic encryption operations for multimedia data that can preserve standard compliance and are friendly to communications and delegate processing. For multimedia authentication, we have discovered the potential key disclosure problem for popular image hashing schemes, and proposed mitigation solutions. In physical-layer wireless communications, we have discovered the threat of signal garbling attack from compromised relay nodes in the emerging cooperative communication paradigm, and proposed a countermeasure to trace and pinpoint the adversarial relay. For the design and deployment of secure sensor communications, we have proposed two sensor location adjustment algorithms for mobility-assisted sensor deployment that can jointly optimize sensing coverage and secure communication connectivity. Furthermore, for general scenarios of group key management, we have proposed a time-efficient key management scheme that can improve the scalability of contributory key management from O(log n) to O(log(log n)) using scheduling and optimization techniques. This dissertation demonstrates that signal processing techniques, along with optimization, scheduling, and beneficial techniques from other related fields of study, can be successfully integrated into security solutions in practical communication systems. The fusion of different technical disciplines can take place at every layer of a secure communication system to strengthen communication security and improve performance-security tradeoff.