This study presents an integrated framework for the automatic generation of the photorealistic 3-d building models from satellite and ground-level imagery. First, the 2-d building patches and the corresponding footprints are extracted from a high resolution imagery using an adaptive fuzzy-genetic algorithm approach. Next, the photorealistic facade textures are automatically extracted from the single ground-level building images using a developed approach, which includes facade image extraction, rectification, and occlusion removal. Finally, the textured 3-d building models are generated automatically by mapping the corresponding textures onto the facades of the models. The developed 2-d building extraction and delineation approach was implemented on a selected urban area of the Batikent district of Ankara, Turkey. The building regions were extracted with an approximate detection rate of 93%. Moreover, the overall delineation accuracy was computed to be 3.9 meters. The developed concept for facade image extraction was tested on two distinct datasets. The facade image extraction accuracies were computed to be 82% and 81% for the Batikent and eTrims datasets, respectively. As to rectification results, 60% and 80% of the facade images provided errors under ten pixels for the Batikent and eTrims datasets, respectively. In the evaluation of occlusion removal, the average scores were computed to be 2.58 and 2.28 for the Batikent and eTrims datasets, respectively. The scores are ranked between 1 (Excellent) to 6 (Unusable). The modeling of the total 110 single buildings with the photorealistic textures took about 50 minutes of processor running time and yielded a satisfactory level of accuracy.

The infiltration of water in asphalt pavements promotes moisture damage primarily through damaging the binder cohesive bond and the adhesive bond between aggregates and binder. Moisture damage is associated with excessive deflection, cracking, and rutting. The first step in addressing the problems caused by the presence of water within pavement systems is quantifying the permeability of hot mix asphalt (HMA) mixes. This dissertation deals with the development of empirical-analytical and numerical approaches for predicting the permeability of HMA. Both approaches rely on the analysis of air void distribution within the HMA microstructure. The empirical-analytical approach relies on the development of modified forms of the Kozeny-Carman equation and determining the material properties involved in this equation through three dimensional microstructure analyses of X-ray Computed Tomography (CT) images. These properties include connected percent air voids (effective porosity), tortuosity, and air void specific surface area. A database of materials and permeability measurements was used to verify the developed predicting equation. The numerical approach, which is the main focus of this study, includes the development of a finite difference numerical simulation model to simulate the steady incompressible fluid flow in HMA. The model uses the non-staggered system that utilizes only one cell to solve for all governing equations, and it is applicable for cell Reynolds number (Rec) values that are not restricted by |Rec|≤2. The validity of the numerical model is verified through comparisons with closed-form solutions for idealized microstructure. The numerical model was used to find the components of the three-dimensional (3-D) permeability tensor and permeability anisotropy values for different types of HMA mixes. It was found that the principal permeability directions values are almost in the horizontal and vertical directions with the maximum permeability being in the horizontal direction.

The architectures of the control devices in active control algorithm are an important fact in civil structural buildings. Traditional research has limitations in finding the optimal architecture of control devices such as using predefined numbers or locations of sensors and dampers within the 2-and 3-dimensional (3-D) model of the structure. Previous research using single-objective optimization only provides limited data for defining the architecture of sensors and control devices. The Linear Quadratic Gaussian (LQG) control algorithm is used as the active control strategy. The American Society of Civil Engineers (ASCE) control benchmark building definition is used to develop the building system model. The proposed gene manipulation genetic algorithm (GMGA) determines the near-optimal Pareto fronts which consist of varying numbers and locations of sensors and control devices for controlling the ASCE benchmark building by considering multi-objectives such as interstory drift and minimizing the number of the control devices. The proposed GMGA reduced the central processing unit (CPU) run time and produced more optimal Pareto fronts for the 2-D and 3-D 20-story building models. Using the GMGA provided several benefits: (1) the possibility to apply any presuggested multi-objective optimization mechanism; (2) the availability to perform a objective optimization problem; (3) the adoptability of the diverse encoding provided by the GA; (4) the possibility of including the engineering judgment in generating the next generation population by using a gene creation mechanisms; and (5) the flexibility of the gene creation mechanism in applying and changing the mechanism dependent on optimization problem. The near-optimal Pareto fronts obtained offer the structural engineer a diverse choice in designing control system and installing the control devices. The locations and numbers of the dampers and sensors in each story are highly dependent on the sensor locations. By providing near-Pareto fronts of possible solutions to the engineer that also consider diverse earthquakes, the engineer can get normalized patterns of architectures of control devices and sensors about random earthquakes.

As a result of everlasting developments in multimedia technologies, all kinds of objects tracking theory using machine vision or image process methods have been proposed. Most of the methods are based on shape of the object. For this reason, the profile of the tracked object must be known in advance. In many situations, we expect to track the object whose shape is unknown but speed or direction is explicit. For instance, speed or moving direction of the object is known. This thesis presents a spatio-temporal tracking technique, which extracts image information depending on speed of the moving object regardless of its shape. Furthermore, combination of the proposed method in spatio-temporal domain and the optical flow scheme makes the whole tracking system even more robust.

In general, stereovision can be defined as a two part problem. The first is the correspondence problem. This involves determining the image point in each image of a set of images that correspond to the same physical point P. We will call this set of image points, N. The second problem is the reconstruction problem. Once a set of image points, N, that correspond to point P has been determined, N is then used to extract three dimensional information about point P. This master's thesis presents three novel solutions to the reconstruction problem. Two of the techniques presented are for detecting the location of a 3-D point and one for detecting a line expressed in a three dimensional coordinate system. These techniques are tested and validated using a unique 3-D finger detection algorithm. The techniques presented are unique because of their simplicity and because they do not require the cameras to be placed in specific locations, orientations or have specific alignments. On the contrary, it will be shown that the techniques presented in this thesis allow the two cameras used to assume almost any relative pose provided that the object of interest is within their field of view. The relative pose of the cameras at a given instant in time, along with basic equations from the perspective image model are used to form a system of equations that when solved, reveal the 3-D coordinates of a particular fixed point of interest or the three dimensional equation of a fixed line of interest. Finally, it will be shown that a single moving camera can successfully perform the same line and point detection accomplished by two cameras by altering the pose of the camera. The results presented in this work are beneficial to any typical stereovision application because of the computational ease in comparison to other point and line reconstruction techniques. But more importantly, this work allows for a single moving camera to perceive three-dimensional position information, which effectively removes the two camera constraint for a stereo vision system. When used with other monocular cues such as texture or color, the work presented in this thesis could be as accurate as binocular stereo vision at interpreting three dimensional information. Thus, this work could potentially increase the three dimensional perception of a robot that normally uses one camera, such as an eye-in-hand robot or a snake like robot.

In der Neurochirurgie werden für die prä-, intra- und postoperative medizinische Bildgebung dreidimensionale Daten unterschiedlicher Modalitäten überlagert, segmentiert und visualisiert. Durch die Verknüpfung der multimodalen Daten erhofft man einen Informationsgewinn für Diagnose und Therapie. Dabei wird großer Wert auf die intuitive Handhabbarkeit und Verständlichkeit der Software gelegt. In einem neu entwickelten 3-D-Planungssystem wird insbesondere die Erfassung komplexer räumlicher Strukturen und die neurochirurgische Operationsplanung durch aktuelle 3-D-Interaktions- und Visualisierungstechnologien vereinfacht. Das Anwendungsspektrum des Systems wird durch die Entwicklung spezieller Algorithmen kontinuierlich erweitert, z. B. der automatischen Segmentierung und elastischen Registrierung von multimodalen Bilddaten, und kann somit an neue klinische Fragestellungen angepasst werden. / In neurosurgery, three-dimensional data from different modalities are registered, segmented and visualised for pre-, intraand post-operative medical imaging. A combination of the multimodal data sets provides additional information for the analyses of anatomic and functional correlations and for surgical planning. For routine use, it is important to design a software application that is simple and intuitive to use. A neurosurgical operation planning system is realised in combination with novel 3D-interaction and visualisation technologies. The development of additional functions, such as automatic segmentation and elastic registration, enhances the usability of the systems to approach further clinical objectives.

This dissertation investigates the use of the harmonic radar technique for passive wireless sensing applications. Issues of DC power consumption, high RF activation power, large node size, and short communication range associated with the existing passive wireless sensing technologies are addressed by the development of novel, completely passive, high efficiency, compact 3-D harmonic sensor nodes. The node transceiver employs a passive frequency doubler to return the second harmonic of the interrogation signal, and electrically-small 3-D antennas to achieve the compactness and high efficiency. The developed nodes fit inside a sphere with a diameter < 3 cm and achieve communication range > 60 m using a 43 dBm EIRP interrogator. Effective modulation is demonstrated experimentally using low cost commercial vibration sensors. To address major challenges associated with long-range, embedded, passive wireless sensing including sensor node identification and remote channel calibration, a 3-D dual-channel transceiver is developed. To the best of the author's knowledge, the presented dual-channel transceiver is the first completely passive design with built-in passive remote channel calibration and identification capabilities, and the presented nodes have the best overall performance among previously published designs, in terms of conversion efficiency, communication range, and occupied volume. To reduce the cost and weight and improve the manufacturing process of the proposed nodes, the 3-D digital additive manufacturing and conformal direct printing technologies are employed. The harmonic interrogator antenna design is also an underlying focus of this work. Different interrogator antenna candidates are developed based on different design approaches. The first approach is based on the use of dual-channel antenna array, where one channel is used for transmission and the second channel is used for reception. Two dual-channel harmonic interrogator antennas that consist of 4-element circular patch antenna arrays and 2-element quasi-Yagi dipole antenna arrays are implemented. The second approach employs mechanically reconfigurable antennas to reduce the size and maintain persistent radiation properties over wide frequency bandwidth. Two mechanical reconfiguration methods are developed; the first method is based on the use of Hoberman's planar foldable linkage to vary the operating frequency of planar circular patch antennas and the second mechanical reconfiguration method is based on the use of a rack and pinion mechanism to reconfigure dual-band slot antennas. The third approach employs a single channel multi-octave Vivaldi antenna to provide the capability to interrogate a large number of harmonic tags that are widely spaced in frequency. To improve the antenna radiation performance over a broad frequency range, a new method based on the introduction of a parasitic elliptical patch in the flare aperture is proposed. This method enables gain and bandwidth improvement compared to what has been reported for Vivaldi antennas with a compact size. To provide the interrogator the capability to steer the radiation beam for locating and tracking sensor nodes, a topology to develop a miniature, non-dispersive switchable 4-bit phase shifter is proposed on the basis of composite right/left handed transmission line unit cells.

Automatic face recognition has attracted the attention of many research institutes, commercial industries, and government agencies in the past few years mainly due to the emergence of numerous applications, such as surveillance, access control to secure facilities, and airport screening. Almost all of the research on the early days of face recognition was focused on using 2-D (intensity/portrait) images of the face. While several sophisticated 2-D solutions have been proposed, unbiased evaluation studies show that their collective performance remains unsatisfactory, and degrades significantly with variations in lighting condition, face position, makeup, or existence of non-neutral facial expressions. Recent developments in 3-D imaging technology has made cheaper, quicker and more reliable acquisition of 3-D facial models a reality. These 3-D facial models contain information about the anatomical structure of the face that remains constant under variable lighting conditions, facial makeup, and pose variations. Thus, researchers are considering to utilize 3-D structure of the face alone or in combination with 2-D information to alleviate inherent limitations of 2-D images and attain better performance. Published 3-D face recognition algorithms have demonstrated promising results confirming the effectiveness of 3-D facial models in dealing with the above mentioned factors contributing to the failure of 2-D face recognition systems. However, the majority of these 3-D algorithms are extensions of conventional 2-D approaches, where intensity images are simply replaced by 3-D models rendered as range images. These algorithms are not specifically tailored to exploit abundant geometric and anthropometric clues available in 3-D facial models. In this dissertation we introduce innovative 3-D and 2-D+3-D facial measurements (features) that effectively describe the geometric characteristics of the corresponding faces. Some of the features described in this dissertation, as well as many features proposed in the literature are defined around or between meaningful facial landmarks (fiducial points). In order to reach our goal of designing an accurate automatic face recognition system, we also propose a novel algorithm combining 3-D (range) and 2-D (portrait) Gabor clues to pinpoint a number of points with meaningful anthropometric definitions with significantly better accuracies than those achievable using a single modality alone. This dissertation is organized as follows. In Chapter 1, various biometric modalities are introduced and the advantages of the facial biometrics over other modalities are discussed. The discussion in Chapter 1 is continued with introduction of the face recognition’s modes of operation followed by some current and potential future applications. The problem statement of this dissertation is also included in this chapter. In Chapter 2, an extensive review of the successful 2-D, 3-D, and 2-D+3-D face recognition algorithms are provided. Chapter 3 presents the details of our innovative 3-D and 2-D+3-D face features, as well as our accurate fiducial point detection algorithm. Conclusions and directions for future extensions are presented in Chapter 4. / text

As nanometer Very Large Scale Integration (VLSI) demands more transistor density to fabricate multi-cores and memory blocks in a limited die size, many researches have been performed to keep Moore's Low in two different ways: 2D geometric shrinking and 3D vertical wafer stacking. For the geometric shrinking, nano patterning with 193nm lithography equipment is one of the most fundamental challenges beyond 22nm while the next-generation lithography, such as Extreme Ultra-Violet (EUV) lithography still faces tremendous challenges for volume production in the near future. As a practical solution, Double Patterning Lithography (DPL) has become a leading candidate for sub-20nm lithography process. Another approach for multi-core integration is 3D wafer stacking with Through Silicon Via (TSV). Computer-Aided-Design (CAD) approaches to enable robust DPL and TSV technology are the main focus of this dissertation. DPL poses new challenges for overlay and layout decomposition. Therefore, overlay induced variation modeling and efficient decomposition for better manufacturability are in great demand. Since the variation of metal space caused by overlay results in coupling capacitance variation, we first model metal spacing variation with individual overlay sources. Then, all overlay sources are considered to determine the worst timing with coupling capacitance variation. Non-parallel pattern caused by overlay is converted to parallel one with equivalent spacing having the same delay to be applicable of a traditional RC extraction flow. Our experiments show that the delay variation due to overlay in DPL can be up to 9.1%, and well decomposed layout can reduce the variability. For DPL layout decomposition, we propose a multi-objective and flexible framework for stitch minimization, balanced density, and overlay compensation, simultaneously. We use a graph theoretic algorithm for minimum stitch insertion and balanced density. Additional decomposition constraints for overlay compensation are obtained by Integer Linear Programming (ILP). Robust contact decomposition can be obtained with additional constraints. With these constraints, global decomposition is performed using a modified Fiduccia-Mattheyses (FM) graph partitioning algorithm. Experimental results show that the proposed framework is highly scalable and fast: we can decompose all 15 benchmark circuits in five minutes in a density balanced fashion, while an ILP-based approach can finish only the smallest five circuits. In addition, we can remove more than 95% of the timing variation induced by overlay for tested structures. Three-dimensional integration has new manufacturing and design challenges such as device variation due to TSV induced stress and timing corner mismatch between different stacked dies. Since TSV fill material and silicon have different Coefficients of Thermal Expansion (CTE), TSV causes silicon deformation due to different temperatures at chip manufacturing and operating. Therefore, the systematic variation due to TSV induced stress should be considered for robust 3D IC design. We propose systematic TSV stress aware timing analysis and show how to optimize layout for better performance. First, a stress contour map with an analytical radial stress model is generated. Then, the tensile stress is converted to hole and electron mobility variations depending on geometric relations between TSVs and transistors. Mobility variation aware cell library and netlist are generated and incorporated in an industrial timing engine for 3D-IC timing analysis. TSV stress induced timing variations can be as much as 10% for an individual cell. As an application for layout optimization, we can exploit the stress-induced mobility enhancement to improve timing on critical cells. We show that stress-aware perturbation could reduce cell delay by up to 14.0% and critical path delay by 6.5% in our test case. Three-dimensional Clock Tree Synthesis (3D CTS) is one of the main design difficulties in 3D integration because clock network is spreading over all tiers. In 3D CTS, timing corner mismatch between tiers is caused because each tier is manufactured in independent process. Therefore, inter-die variation should be considered to analyze and optimize for paths spreading over several tiers in 3D CTS. In addition, mobility variation of a clock buffer due to stress from TSV can cause unexpected skew which degrades overall chip performance. Therefore, we propose clock period optimization to consider both timing corner mismatch and TSV induced stress. In our experiments, we show that our clock buffer tier assignment reduces clock period variation up to 34.2%, and the most of stress-induced skew can be removed by our stress-aware CTS. Overall, we show that performance gain can be up to 5.7% with the proposed CTS algorithm. As technology scaling continues toward 14nm and 3D-integration, this dissertation addresses several key issues in the design-manufacturing interface, and proposes unified analysis and optimization techniques for effective design and manufacturing integration. / text

The aggressive scaling of the semiconductor technology following the Moore’s Law has delivered true system-on-chip (SoC) integration. Network-on-chip (NoC) has been recently introduced as an effective solution for scalable on-chip communication since dedicated point-to-point (P2P) interconnection and shared bus architecture become performance and power bottlenecks in the SoCs. This dissertation studies three critical NoC challenges such as latency, power, and compatibility with emerging technologies in aspect of an architecture and physical design level. Latency is a key issue in NoC since the performance of applications considerably depends on resource sharing policies employed in an on-chip network. NoCs have been mainly developed to improve network-level performance that captures the inherent performance characteristics of a network itself, but the network-level optimizations are not directly related to application- or system-level performance. In addition, memory latency on NoC critically affects the performance of applications or systems. We propose a synchronous dynamic random access memory (SDRAM) aware NoC design to optimize memory throughput, latency, and design complexity. Furthermore, it is extended to an application-aware NoC design to provide the quality-of-service (QoS) of memory for various applications. NoC provides great on-chip communication. However, it brings no true relief to power budget when the on-chip network scales in terms of complexity/size and signal bandwidth. The combination of NoC and other techniques has the potential to reduce power. We study two power saving research topics for NoC: (a) we propose a voltage-frequency island (VFI) aware NoC optimization framework with a better tradeoff between power efficiency and design complexity to minimize both computation and on-chip communication power. (b) We formulate an application mapping problem to mixed integer quadratic programming (MIQP) with the purpose of reducing power consumption in various hard networks and develop highly efficient algorithms for the MIQP. Regarding NoC compatible with new technologies, we focus on three dimensional (3D) die integration based on through-silicon vias (TSVs). Since an on-chip network design has been subject to not only application constraints but also design/manufacturing constraints, a 3D NoC design is required for innovation in interconnection networks. We propose a chemical-mechanical polishing (CMP) aware application-specific 3D NoC design that minimizes TSV height variation, thus reduces bonding failure, and meanwhile optimizes conventional NoC design objectives such as hop count, wirelength, power, and area. / text