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- Genre: Doctoral Dissertation
- Creators: Li, Baoxin
- Creators: Yu, Hongbin
- Creators: Xue, Guoliang
Description
Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key contributing factors, such as pose, view angle, and body shape, in the generation of the image observations. Experimental results have shown that the resulting pose features extracted using the proposed methods exhibit excellent invariance properties to changes in view angles and body shapes. Furthermore, using the proposed invariant multifactor pose features, a suite of simple while effective algorithms have been developed to solve the movement recognition and pose estimation problems. Using these proposed algorithms, excellent human movement analysis results have been obtained, and most of them are superior to those obtained from state-of-the-art algorithms on the same testing datasets. Moreover, a number of key movement analysis challenges, including robust online gesture spotting and multi-camera gesture recognition, have also been addressed in this research. To this end, an online gesture spotting framework has been developed to automatically detect and learn non-gesture movement patterns to improve gesture localization and recognition from continuous data streams using a hidden Markov network. In addition, the optimal data fusion scheme has been investigated for multicamera gesture recognition, and the decision-level camera fusion scheme using the product rule has been found to be optimal for gesture recognition using multiple uncalibrated cameras. Furthermore, the challenge of optimal camera selection in multi-camera gesture recognition has also been tackled. A measure to quantify the complementary strength across cameras has been proposed. Experimental results obtained from a real-life gesture recognition dataset have shown that the optimal camera combinations identified according to the proposed complementary measure always lead to the best gesture recognition results.
ContributorsPeng, Bo (Author) / Qian, Gang (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
A workload-aware low-power neuromorphic controller for dynamic power and thermal management in VLSI systems is presented. The neuromorphic controller predicts future workload and temperature values based on the past values and CPU performance counters and preemptively regulates supply voltage and frequency. System-level measurements from stateof-the-art commercial microprocessors are used to get workload, temperature and CPU performance counter values. The controller is designed and simulated using circuit-design and synthesis tools. At device-level, on-chip planar inductors suffer from low inductance occupying large chip area. On-chip inductors with integrated magnetic materials are designed, simulated and fabricated to explore performance-efficiency trade offs and explore potential applications such as resonant clocking and on-chip voltage regulation. A system level study is conducted to evaluate the effect of on-chip voltage regulator employing magnetic inductors as the output filter. It is concluded that neuromorphic power controller is beneficial for fine-grained per-core power management in conjunction with on-chip voltage regulators utilizing scaled magnetic inductors.
ContributorsSinha, Saurabh (Author) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Yu, Hongbin (Committee member) / Christen, Jennifer B. (Committee member) / Arizona State University (Publisher)
Created2011
Description
There are many wireless communication and networking applications that require high transmission rates and reliability with only limited resources in terms of bandwidth, power, hardware complexity etc.. Real-time video streaming, gaming and social networking are a few such examples. Over the years many problems have been addressed towards the goal of enabling such applications; however, significant challenges still remain, particularly, in the context of multi-user communications. With the motivation of addressing some of these challenges, the main focus of this dissertation is the design and analysis of capacity approaching coding schemes for several (wireless) multi-user communication scenarios. Specifically, three main themes are studied: superposition coding over broadcast channels, practical coding for binary-input binary-output broadcast channels, and signalling schemes for two-way relay channels. As the first contribution, we propose an analytical tool that allows for reliable comparison of different practical codes and decoding strategies over degraded broadcast channels, even for very low error rates for which simulations are impractical. The second contribution deals with binary-input binary-output degraded broadcast channels, for which an optimal encoding scheme that achieves the capacity boundary is found, and a practical coding scheme is given by concatenation of an outer low density parity check code and an inner (non-linear) mapper that induces desired distribution of "one" in a codeword. The third contribution considers two-way relay channels where the information exchange between two nodes takes place in two transmission phases using a coding scheme called physical-layer network coding. At the relay, a near optimal decoding strategy is derived using a list decoding algorithm, and an approximation is obtained by a joint decoding approach. For the latter scheme, an analytical approximation of the word error rate based on a union bounding technique is computed under the assumption that linear codes are employed at the two nodes exchanging data. Further, when the wireless channel is frequency selective, two decoding strategies at the relay are developed, namely, a near optimal decoding scheme implemented using list decoding, and a reduced complexity detection/decoding scheme utilizing a linear minimum mean squared error based detector followed by a network coded sequence decoder.
ContributorsBhat, Uttam (Author) / Duman, Tolga M. (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Li, Baoxin (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Bridging semantic gap is one of the fundamental problems in multimedia computing and pattern recognition. The challenge of associating low-level signal with their high-level semantic interpretation is mainly due to the fact that semantics are often conveyed implicitly in a context, relying on interactions among multiple levels of concepts or low-level data entities. Also, additional domain knowledge may often be indispensable for uncovering the underlying semantics, but in most cases such domain knowledge is not readily available from the acquired media streams. Thus, making use of various types of contextual information and leveraging corresponding domain knowledge are vital for effectively associating high-level semantics with low-level signals with higher accuracies in multimedia computing problems. In this work, novel computational methods are explored and developed for incorporating contextual information/domain knowledge in different forms for multimedia computing and pattern recognition problems. Specifically, a novel Bayesian approach with statistical-sampling-based inference is proposed for incorporating a special type of domain knowledge, spatial prior for the underlying shapes; cross-modality correlations via Kernel Canonical Correlation Analysis is explored and the learnt space is then used for associating multimedia contents in different forms; model contextual information as a graph is leveraged for regulating interactions among high-level semantic concepts (e.g., category labels), low-level input signal (e.g., spatial/temporal structure). Four real-world applications, including visual-to-tactile face conversion, photo tag recommendation, wild web video classification and unconstrained consumer video summarization, are selected to demonstrate the effectiveness of the approaches. These applications range from classic research challenges to emerging tasks in multimedia computing. Results from experiments on large-scale real-world data with comparisons to other state-of-the-art methods and subjective evaluations with end users confirmed that the developed approaches exhibit salient advantages, suggesting that they are promising for leveraging contextual information/domain knowledge for a wide range of multimedia computing and pattern recognition problems.
ContributorsWang, Zhesheng (Author) / Li, Baoxin (Thesis advisor) / Sundaram, Hari (Committee member) / Qian, Gang (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2011
Description
CMOS technology is expected to enter the 10nm regime for future integrated circuits (IC). Such aggressive scaling leads to vastly increased variability, posing a grand challenge to robust IC design. Variations in CMOS are often divided into two types: intrinsic variations and process-induced variations. Intrinsic variations are limited by fundamental physics. They are inherent to CMOS structure, considered as one of the ultimate barriers to the continual scaling of CMOS devices. In this work the three primary intrinsic variations sources are studied, including random dopant fluctuation (RDF), line-edge roughness (LER) and oxide thickness fluctuation (OTF). The research is focused on the modeling and simulation of those variations and their scaling trends. Besides the three variations, a time dependent variation source, Random Telegraph Noise (RTN) is also studied. Different from the other three variations, RTN does not contribute much to the total variation amount, but aggregate the worst case of Vth variations in CMOS. In this work a TCAD based simulation study on RTN is presented, and a new SPICE based simulation method for RTN is proposed for time domain circuit analysis. Process-induced variations arise from the imperfection in silicon fabrication, and vary from foundries to foundries. In this work the layout dependent Vth shift due to Rapid-Thermal Annealing (RTA) are investigated. In this work, we develop joint thermal/TCAD simulation and compact modeling tools to analyze performance variability under various layout pattern densities and RTA conditions. Moreover, we propose a suite of compact models that bridge the underlying RTA process with device parameter change for efficient design optimization.
ContributorsYe, Yun, Ph.D (Author) / Cao, Yu (Thesis advisor) / Yu, Hongbin (Committee member) / Song, Hongjiang (Committee member) / Clark, Lawrence (Committee member) / Arizona State University (Publisher)
Created2011
Description
A statement appearing in social media provides a very significant challenge for determining the provenance of the statement. Provenance describes the origin, custody, and ownership of something. Most statements appearing in social media are not published with corresponding provenance data. However, the same characteristics that make the social media environment challenging, including the massive amounts of data available, large numbers of users, and a highly dynamic environment, provide unique and untapped opportunities for solving the provenance problem for social media. Current approaches for tracking provenance data do not scale for online social media and consequently there is a gap in provenance methodologies and technologies providing exciting research opportunities. The guiding vision is the use of social media information itself to realize a useful amount of provenance data for information in social media. This departs from traditional approaches for data provenance which rely on a central store of provenance information. The contemporary online social media environment is an enormous and constantly updated "central store" that can be mined for provenance information that is not readily made available to the average social media user. This research introduces an approach and builds a foundation aimed at realizing a provenance data capability for social media users that is not accessible today.
ContributorsBarbier, Geoffrey P (Author) / Liu, Huan (Thesis advisor) / Bell, Herbert (Committee member) / Li, Baoxin (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
Semiconductor nanowires (NWs) are one dimensional materials and have size quantization effect when the diameter is sufficiently small. They can serve as optical wave guides along the length direction and contain optically active gain at the same time. Due to these unique properties, NWs are now very promising and extensively studied for nanoscale optoelectronic applications. A systematic and comprehensive optical and microstructural study of several important infrared semiconductor NWs is presented in this thesis, which includes InAs, PbS, InGaAs, erbium chloride silicate and erbium silicate. Micro-photoluminescence (PL) and transmission electron microscope (TEM) were utilized in conjunction to characterize the optical and microstructure of these wires. The focus of this thesis is on optical study of semiconductor NWs in the mid-infrared wavelengths. First, differently structured InAs NWs grown using various methods were characterized and compared. Three main PL peaks which are below, near and above InAs bandgap, respectively, were observed. The octadecylthiol self-assembled monolayer was employed to passivate the surface of InAs NWs to eliminate or reduce the effects of the surface states. The band-edge emission from wurtzite-structured NWs was completely recovered after passivatoin. The passivated NWs showed very good stability in air and under heat. In the second part, mid-infrared optical study was conducted on PbS wires of subwavelength diameter and lasing was demonstrated under optical pumping. The PbS wires were grown on Si substrate using chemical vapor deposition and have a rock-salt cubic structure. Single-mode lasing at the wavelength of ~3000-4000 nm was obtained from single as-grown PbS wire up to the temperature of 115 K. PL characterization was also utilized to demonstrate the highest crystallinity of the vertical arrays of InP and InGaAs/InP composition-graded heterostructure NWs made by a top-down fabrication method. TEM-related measurements were performed to study the crystal structures and elemental compositions of the Er-compound core-shell NWs. The core-shell NWs consist of an orthorhombic-structured erbium chloride silicate shell and a cubic-structured silicon core. These NWs provide unique Si-compatible materials with emission at 1530 nm for optical communications and solid state lasers.
ContributorsSun, Minghua (Author) / Ning, Cun-Zheng (Thesis advisor) / Yu, Hongbin (Committee member) / Carpenter, Ray W. (Committee member) / Johnson, Shane (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-label learning, which deals with data associated with multiple labels simultaneously, is ubiquitous in real-world applications. To overcome the curse of dimensionality in multi-label learning, in this thesis I study multi-label dimensionality reduction, which extracts a small number of features by removing the irrelevant, redundant, and noisy information while considering the correlation among different labels in multi-label learning. Specifically, I propose Hypergraph Spectral Learning (HSL) to perform dimensionality reduction for multi-label data by exploiting correlations among different labels using a hypergraph. The regularization effect on the classical dimensionality reduction algorithm known as Canonical Correlation Analysis (CCA) is elucidated in this thesis. The relationship between CCA and Orthonormalized Partial Least Squares (OPLS) is also investigated. To perform dimensionality reduction efficiently for large-scale problems, two efficient implementations are proposed for a class of dimensionality reduction algorithms, including canonical correlation analysis, orthonormalized partial least squares, linear discriminant analysis, and hypergraph spectral learning. The first approach is a direct least squares approach which allows the use of different regularization penalties, but is applicable under a certain assumption; the second one is a two-stage approach which can be applied in the regularization setting without any assumption. Furthermore, an online implementation for the same class of dimensionality reduction algorithms is proposed when the data comes sequentially. A Matlab toolbox for multi-label dimensionality reduction has been developed and released. The proposed algorithms have been applied successfully in the Drosophila gene expression pattern image annotation. The experimental results on some benchmark data sets in multi-label learning also demonstrate the effectiveness and efficiency of the proposed algorithms.
ContributorsSun, Liang (Author) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Liu, Huan (Committee member) / Mittelmann, Hans D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-task learning (MTL) aims to improve the generalization performance (of the resulting classifiers) by learning multiple related tasks simultaneously. Specifically, MTL exploits the intrinsic task relatedness, based on which the informative domain knowledge from each task can be shared across multiple tasks and thus facilitate the individual task learning. It is particularly desirable to share the domain knowledge (among the tasks) when there are a number of related tasks but only limited training data is available for each task. Modeling the relationship of multiple tasks is critical to the generalization performance of the MTL algorithms. In this dissertation, I propose a series of MTL approaches which assume that multiple tasks are intrinsically related via a shared low-dimensional feature space. The proposed MTL approaches are developed to deal with different scenarios and settings; they are respectively formulated as mathematical optimization problems of minimizing the empirical loss regularized by different structures. For all proposed MTL formulations, I develop the associated optimization algorithms to find their globally optimal solution efficiently. I also conduct theoretical analysis for certain MTL approaches by deriving the globally optimal solution recovery condition and the performance bound. To demonstrate the practical performance, I apply the proposed MTL approaches on different real-world applications: (1) Automated annotation of the Drosophila gene expression pattern images; (2) Categorization of the Yahoo web pages. Our experimental results demonstrate the efficiency and effectiveness of the proposed algorithms.
ContributorsChen, Jianhui (Author) / Ye, Jieping (Thesis advisor) / Kumar, Sudhir (Committee member) / Liu, Huan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2011
Description
With increasing demand for System on Chip (SoC) and System in Package (SiP) design in computer and communication technologies, integrated inductor which is an essential passive component has been widely used in numerous integrated circuits (ICs) such as in voltage regulators and RF circuits. In this work, soft ferromagnetic core material, amorphous Co-Zr-Ta-B, was incorporated into on-chip and in-package inductors in order to scale down inductors and improve inductors performance in both inductance density and quality factor. With two layers of 500 nm Co-Zr-Ta-B films a 3.5X increase in inductance and a 3.9X increase in quality factor over inductors without magnetic films were measured at frequencies as high as 1 GHz. By laminating technology, up to 9.1X increase in inductance and more than 5X increase in quality factor (Q) were obtained from stripline inductors incorporated with 50 nm by 10 laminated films with a peak Q at 300 MHz. It was also demonstrated that this peak Q can be pushed towards high frequency as far as 1GHz by a combination of patterning magnetic films into fine bars and laminations. The role of magnetic vias in magnetic flux and eddy current control was investigated by both simulation and experiment using different patterning techniques and by altering the magnetic via width. Finger-shaped magnetic vias were designed and integrated into on-chip RF inductors improving the frequency of peak quality factor from 400 MHz to 800 MHz without sacrificing inductance enhancement. Eddy current and magnetic flux density in different areas of magnetic vias were analyzed by HFSS 3D EM simulation. With optimized magnetic vias, high frequency response of up to 2 GHz was achieved. Furthermore, the effect of applied magnetic field on on-chip inductors was investigated for high power applications. It was observed that as applied magnetic field along the hard axis (HA) increases, inductance maintains similar value initially at low fields, but decreases at larger fields until the magnetic films become saturated. The high frequency quality factor showed an opposite trend which is correlated to the reduction of ferromagnetic resonant absorption in the magnetic film. In addition, experiments showed that this field-dependent inductance change varied with different patterned magnetic film structures, including bars/slots and fingers structures. Magnetic properties of Co-Zr-Ta-B films on standard organic package substrates including ABF and polyimide were also characterized. Effects of substrate roughness and stress were analyzed and simulated which provide strategies for integrating Co-Zr-Ta-B into package inductors and improving inductors performance. Stripline and spiral inductors with Co-Zr-Ta-B films were fabricated on both ABF and polyimide substrates. Maximum 90% inductance increase in hundreds MHz frequency range were achieved in stripline inductors which are suitable for power delivery applications. Spiral inductors with Co-Zr-Ta-B films showed 18% inductance increase with quality factor of 4 at frequency up to 3 GHz.
ContributorsWu, Hao (Author) / Yu, Hongbin (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Cao, Yu (Committee member) / Chickamenahalli, Shamala (Committee member) / Arizona State University (Publisher)
Created2013