Dendritic shapes are commonplace in the natural world such as trees, lichens, coral and lightning. Models of dendritic shapes are widely needed in many areas. Because of their branching fractal and erratic structures modeling dendritic shapes is a tricky task. Existing methods for modeling dendritic shapes are slow and complicated.<p>In this thesis we present a procedural algorithm of using path planning to model dendritic shapes. We generate a dendrite by finding the least-cost paths from multiple endpoints to a common generator and use the dendrite to build the geometric model. With the control handles of endpoint placement, fractal shape, edge weights distribution and path width, we create different shapes of dendrites that simulate different kinds of dendritic shapes very well. Compared with some existing methods, our algorithm is fast and simple.

In this thesis, we present a detailed analysis of the conventions that appear in fictional spaceship design, including a discussion of their origins, their uses in emulating certain traits, and reasons these conventions might be followed or ignored. We uncover these conventions by examining and comparing popular spaceship designs from the past sixty years, which we present in a detailed survey. We also examine an aesthetic interpretation of information theory, which can be used to describe the balance of uniformity amidst variety, and discuss specific strategies for incorporating these principles into the creation of spaceship surface details. Procedural modeling describes a set of techniques used to allow computers to generate digital content such as 3D digital models automatically. However, procedural modeling to date has focused on very specific areas: natural scenery such as trees and terrain, or cityscapes such as road maps and buildings. While these types of models are important and useful, they focus on a specific subset of the procedural modeling problem. Though procedural generation can be an invaluable tool for providing viable and dynamic content, it is troubling that so few types of objects have been studied in this area. Using the aesthetic and spaceship principles we define, we have developed a prototype system to procedurally generate the surface details of a large scale spaceship. Given a surface representing the frame of a spaceship, we apply geometry automatically in a coherent manner to achieve the appearance of a spaceship by emulating important traits.

In this thesis, we present a detailed analysis of the conventions that appear in fictional spaceship design, including a discussion of their origins, their uses in emulating certain traits, and reasons these conventions might be followed or ignored. We uncover these conventions by examining and comparing popular spaceship designs from the past sixty years, which we present in a detailed survey. We also examine an aesthetic interpretation of information theory, which can be used to describe the balance of uniformity amidst variety, and discuss specific strategies for incorporating these principles into the creation of spaceship surface details. Procedural modeling describes a set of techniques used to allow computers to generate digital content such as 3D digital models automatically. However, procedural modeling to date has focused on very specific areas: natural scenery such as trees and terrain, or cityscapes such as road maps and buildings. While these types of models are important and useful, they focus on a specific subset of the procedural modeling problem. Though procedural generation can be an invaluable tool for providing viable and dynamic content, it is troubling that so few types of objects have been studied in this area. Using the aesthetic and spaceship principles we define, we have developed a prototype system to procedurally generate the surface details of a large scale spaceship. Given a surface representing the frame of a spaceship, we apply geometry automatically in a coherent manner to achieve the appearance of a spaceship by emulating important traits.

Dendritic shapes are commonplace in the natural world such as trees, lichens, coral and lightning. Models of dendritic shapes are widely needed in many areas. Because of their branching fractal and erratic structures modeling dendritic shapes is a tricky task. Existing methods for modeling dendritic shapes are slow and complicated.<p>In this thesis we present a procedural algorithm of using path planning to model dendritic shapes. We generate a dendrite by finding the least-cost paths from multiple endpoints to a common generator and use the dendrite to build the geometric model. With the control handles of endpoint placement, fractal shape, edge weights distribution and path width, we create different shapes of dendrites that simulate different kinds of dendritic shapes very well. Compared with some existing methods, our algorithm is fast and simple.

Training typically begins with a pre-existing scenario. The training exercise is performed and then an after action review is sometimes held. This “training pipeline” is repeated for each scenario that will be used that day. This approach is used routinely and often effectively, yet it has a number of aspects that can result in poor training. In particular, this process commonly has two associated events that are undesirable. First, scenarios are re-used over and over, which can reduce their effectiveness in training. Second, additional responsibility is placed on the individual training facilitator in that the trainer must now track performance improvements between scenarios. Taking both together can result in a multiplicative degradation in effectiveness. Within any simulation training exercise, a scenario definition is the starting point. While these are, unfortunately, re-used and over-used, they can, in fact, be generated from scratch each time. Typically, scenarios include the entire configuration for the simulators such as entities used, time of day, weather effects, entity starting locations and, where applicable, munitions effects. In addition, a background story (exercise briefing) is given to the trainees. The leader often then develops a mission plan that is shared with the trainee group. Given all of these issues, scientists began to explore more purposeful, targeted training. Rather than an ad-hoc creation of a simulation experience, there was an increased focus on the content of the experience and its effects on training. Previous work in scenario generation, interactive storytelling and computational approaches, while providing a good foundation, fall short on addressing the need for iv adaptive, automatic scenario generation. This dissertation addresses this need by building up a conceptual model to represent scenarios, mapping that conceptual model to a computational model, and then applying a newer procedural modeling technique, known as Functional L-systems, to create scenarios given a training objective, scenario complexity level desired, and sets of baseline and vignette scenario facets. A software package, known as PYTHAGORAS, was built and is presented that incorporates all these contributions into an actual tool for creating scenarios (both manual and automatic approaches are included). This package is then evaluated by subject matter experts in a scenario-based “Turing Test” of sorts where both system-generated scenarios and human-generated scenarios are evaluated by independent reviewers. The results are presented from various angles. Finally, a review of how such a tool can affect the training pipeline is included. In addition, a number of areas into which scenario generation can be expanded are reviewed. These focus on additional elements of both the training environment (e.g., buildings, interiors, etc.) and the training process (e.g., scenario write-ups, etc.).

The idea that a complex object can be decomposed into simpler parts is fundamental to 3D design, so it is clearly desirable that digital representations of 3D shapes incorporate this part information. While solid modeling techniques based on set-theoretic volumetric composition intrinsically support hierarchical part-based shape descriptions, organic objects such as a human vertebra are more efficiently represented by surface modeling techniques. And although a human observer will easily identify part decompositions in surface models, the homogenous graphs of connected points and edges used in surface representations do not readily support explicit part decompositions. In this thesis, I will develop a part-based representation for 3D surface models. In abstract mathematics, a surface part can be represented as a deformation of a Riemannian manifold. To create a practical implementation, it is necessary to define representations of the 3D part shape and the region on the target surface where the part is to be placed. To represent the part region I will develop the Discrete Exponential Map (DEM), an algorithm which approximates the intrinsic normal coordinates on manifolds. To support arbitrary part shapes I will develop the COILS surface deformation, a robust geometric differential representation of point-sampled surfaces. Based on this part definition, I will then propose the Surface Tree, which makes possible the representation of complex shapes via a procedural, hierarchical composition of surface parts, analogous to the trees used in solid modeling. A major theme throughout the thesis is that part-based approaches have the potential to make surface design interfaces significantly more efficient and expressive. To explore this question and demonstrate the utility of my technical contributions, I present three novel modeling tools: an interactive texture design interface, a drag-and-drop mesh composition tool, and a sketch-based Surface Tree modeling environment. In addition to comparative algorithmic evaluations, and a consideration of representational capabilities, I have evaluated this body of work by publicly distributing my modeling tools. I will close the thesis with a discussion of the extensive feedback provided by users of my drag-and-drop mesh composition tool, called meshmixer. This feedback suggests that part-based approaches have significant benefits for surface modeling.

The idea that a complex object can be decomposed into simpler parts is fundamental to 3D design, so it is clearly desirable that digital representations of 3D shapes incorporate this part information. While solid modeling techniques based on set-theoretic volumetric composition intrinsically support hierarchical part-based shape descriptions, organic objects such as a human vertebra are more efficiently represented by surface modeling techniques. And although a human observer will easily identify part decompositions in surface models, the homogenous graphs of connected points and edges used in surface representations do not readily support explicit part decompositions. In this thesis, I will develop a part-based representation for 3D surface models. In abstract mathematics, a surface part can be represented as a deformation of a Riemannian manifold. To create a practical implementation, it is necessary to define representations of the 3D part shape and the region on the target surface where the part is to be placed. To represent the part region I will develop the Discrete Exponential Map (DEM), an algorithm which approximates the intrinsic normal coordinates on manifolds. To support arbitrary part shapes I will develop the COILS surface deformation, a robust geometric differential representation of point-sampled surfaces. Based on this part definition, I will then propose the Surface Tree, which makes possible the representation of complex shapes via a procedural, hierarchical composition of surface parts, analogous to the trees used in solid modeling. A major theme throughout the thesis is that part-based approaches have the potential to make surface design interfaces significantly more efficient and expressive. To explore this question and demonstrate the utility of my technical contributions, I present three novel modeling tools: an interactive texture design interface, a drag-and-drop mesh composition tool, and a sketch-based Surface Tree modeling environment. In addition to comparative algorithmic evaluations, and a consideration of representational capabilities, I have evaluated this body of work by publicly distributing my modeling tools. I will close the thesis with a discussion of the extensive feedback provided by users of my drag-and-drop mesh composition tool, called meshmixer. This feedback suggests that part-based approaches have significant benefits for surface modeling.

Digitization and characterization of urban spaces are essential components as we move to an ever-growing ’always connected’ world. Accurate analysis of such digital urban spaces has become more important as we continue to get spatial and social context-aware feedback and recommendations in our daily activities. Modeling and reconstruction of urban environments have thus gained unprecedented importance in the last few years. Such analysis typically spans multiple disciplines, such as computer graphics, and computer vision as well as architecture, geoscience, and remote sensing. Reconstructing an urban environment usually requires an entire pipeline consisting of different tasks. In such a pipeline, data analysis plays a strong role in acquiring meaningful insights from the raw data. This dissertation primarily focuses on the analysis of various forms of urban data and proposes a set of techniques to extract useful information, which is then used for different applications. The first part of this dissertation presents a semi-automatic framework to analyze facade images to recover individual windows along with their functional configurations such as open or (partially) closed states. The main advantage of recovering both the repetition patterns of windows and their individual deformation parameters is to produce a factored facade representation. Such a factored representation enables a range of applications including interactive facade images, improved multi-view stereo reconstruction, facade-level change detection, and novel image editing possibilities. The second part of this dissertation demonstrates the importance of a layout configuration on its performance. As a specific application scenario, I investigate the interior layout of warehouses wherein the goal is to assign items to their storage locations while reducing flow congestion and enhancing the speed of order picking processes. The third part of the dissertation proposes a method to classify cities based on their functional behavior. Commonly used computational approaches concentrate on geometric descriptors, for both images and laser scans. Instead, I analyze street networks, both their topology (i.e., connectivity) and geometry (i.e., layout), in an attempt to understand the factors that play dominant roles in determining the characteristic of cities. A set of street network descriptors is proposed to capture the essence of city layouts and used, in a supervised setting, to classify and categorize various cities across the world. Each part of the dissertation shows the utility of the proposed methods through describing a variety of applications on different examples.

Master of Landscape Architecture / Department of Landscape Architecture/Regional and Community Planning / Brent Chamberlain / 3D interactive visualizations can communicate complex urban design ideas to communities to improve planning (Bertol & Foell, 1997; Bishop et al., 2008; Griffon et al., 2011; Lange & Bishop, 2005). Unfortunately, many landscape architects, urban designers, and city planners currently re-frame from using such gaming technology capable of creating 3D interactive visualizations (Deane, 2015a). Many firms use verbal descriptions with images. This method is insufficient for facilitating feedback (Bratteteig & Wagner, 2010; Gordon, et al, 2010; Stakeholder Engagement, 2009; Zhang, 2004). According to Lange and Bishop (2005) there is no reason why real-time visualizations should not be used in urban design. Design fields will be moving toward procedural modeling software that is code-based to quickly model urban development (Flachbart & Weibel, 2005). However, this type of software, i.e., ESRI CityEngine, is only being used by approximately 10% of firms (Deane, 2015a). This paper is one of the first to analyze how ESRI CityEngine can be used and improved to support the workflow of landscape architects, urban designers, and planners for urban development projects. The project explored ESRI CityEngine’s procedural modeling and metric capabilities, and how it could be used to visualize a proposed Urban Core Residential District in Manhattan, Kansas. This process involved applying CGA (computer generated architecture) rules to GIS data, to model trees, streetscapes, landscapes, and buildings. Visuals that were produced include a CityEngine Web Scene and a Unity game.

The use of Procedural Modeling for the creation of 3D models such as Buildings, Terrains, Trees etc., is becoming increasingly common in Films, Video Games, Urban Modeling and Architectural Visualization. This is due to the primary factor that using procedural models in comparison to traditional hand-modeled models helps in saving time, cost and aids in generation of a larger variety in comparison to a few. However, there are so many open problems in procedural modeling methods that does not rely on any user assistance or aid in generating models especially in terms of their visual quality and perception. Although, it is easy to identify realistic looking models from procedural models, the metrics that make them ’Real’ or ’Procedural’ is still in the indeterminable and remains uncanny in nature. The perceptual metrics (intrinsic factors such as surface features and details, extrinsic factors such as environmental attributes and visual cues) that contributes to the visual perception of Procedural models have not been studied in detail or quantified yet. This dissertation presents a first step in the direction of perceptual evaluation of procedural models of terrains. We gathered and categorized several types of real and synthetic terrains generated by methods used in computer graphics and conducted two large studies with 70 participants ranking them perceptually.<br><br>The results show that synthetic terrains lack in visual quality and are perceived worse than real terrains with statistical significance. We performed a quantitative study by using localized geomorphology based landform features on terrains (geomorphons) that indicate that valleys, ridges, and hollows have significant perceptual importance. We then used generative deep generative neural network to transfer the features from real terrains to synthetic ones and vice versa to further confirm their importance. A second perceptual experiment with 128 participants confirmed the importance of the transferred features for visual perception. Based on these results, we introduce PTQM (Perceived Terrain Quality Metrics); a novel perceptual metrics based on geomorphons that assigns a number of estimated visual quality of a terrain represented as a digital elevation map. The introduced perceptual metric based on geomorphons indicate that features such as Valley (0.66), Ridge (0.64), Summit (0.44), Depression (0.42), Spur(0.33), and Hollow (0.22) in order have significant perceptual importance. By using linear regression, we show that the presented features are strongly correlated with perceived visual quality.<br>