GEOMETRIC ANALYSIS TOOLS FOR MESH SEGMENTATION

Surface segmentation, a process which divides a surface into parts, is the basis for many surface manipulation applications which include model metamorphosis, model simplifica- tion, model retrieval, model alignment and texture mapping. This dissertation discusses novel methods for geometric surface analysis and segmentation and applications for these methods. Novel work within this dissertation includes a new 3D mesh segmentation algo- rithm which is referred to as the ridge-walking algorithm. The main benefit of this algo- rithm is that it can dynamically change the criteria it uses to identify surface parts which allows the algorithm to be adjusted to suit different types of surfaces and different segmen- tation goals. The dynamic segmentation behavior allows users to extract three different types of surface regions: (1) regions delineated by convex ridges, (2) regions delineated by concave valleys, and (3) regions delineated by both concave and convex curves. The ridge walking algorithm is quantitatively evaluated by comparing it with competing algo- rithms and human-generated segmentations. The evaluation is accompanied with a detailed geometrical analysis of a select subset of segmentation results to facilitate a better under- standing of the strengths and weaknesses of this algorithm. The ridge walking algorithm is applied to three domain-specific segmentation prob- lems. The first application uses this algorithm to partition bone fragment surfaces into three semantic parts: (1) the fracture surface, (2) the periosteal surface and (3) the articular surface. Segmentation of bone fragments is an important computational step necessary in developing quantitative methods for bone fracture analysis and for creating computational tools for virtual fracture reconstruction. The second application modifies the 3D ridge walking algorithm so that it can be applied to 2D images. In this case, the 2D image is modeled as a Monge patch and principal curvatures of the intensity surface are computed iv for each image pixel. These principal curvatures are then used by ridge walking algorithm to segment the image into meaningful parts. The third application uses the ridge walking algorithm to facilitate analysis of virtual 3D terrain models. Specifically, the algorithm is integrated as a part of a larger software system designed to enable users to browse, visualize and analyze 3D geometric data generated by NASA’s Mars Exploratory Rovers Spirit and Opportunity. In this context, the ridge walking algorithm is used to identify surface features such as rocks in the terrain models

Piecewise Linear Patch Reconstruction for Segmentation and Description of Non-smooth Image Structures

In this paper, we propose a unified energy minimization model for the segmentation of non-smooth image structures. The energy of piecewise linear patch reconstruction is considered as an objective measure of the quality of the segmentation of non-smooth structures. The segmentation is achieved by minimizing the single energy without any separate process of feature extraction. We also prove that the error of segmentation is bounded by the proposed energy functional, meaning that minimizing the proposed energy leads to reducing the error of segmentation. As a by-product, our method produces a dictionary of optimized orthonormal descriptors for each segmented region. The unique feature of our method is that it achieves the simultaneous segmentation and description for non-smooth image structures under the same optimization framework. The experiments validate our theoretical claims and show the clear superior performance of our methods over other related methods for segmentation of various image textures. We show that our model can be coupled with the piecewise smooth model to handle both smooth and non-smooth structures, and we demonstrate that the proposed model is capable of coping with multiple different regions through the one-against-all strategy

Development of Optimal Material Extrusion Additive Manufacturing Tool Path Parameters for Minimizing Void Regions Using Contemporary Tool Path Solutions

A problem with the planning solutions for the additive manufacturing material extrusion process is a lack of optimization strategies to improve upon the standard raster and contour toolpaths. After experimental testing, it was recognized that a component’s strength relationship with respect to the volume of material usage is inconsistent and that failures occurred in regions of voids. From previous studies, it was found that a build orientation in the material extrusion process influences the support material requirements, processing time, surface finish, voids volume, etc. This dissertation aims to identify, minimize, and manage void regions during the toolpath generation, and studies the effects of build orientation on the amount and location of unwanted voids in the finished part. This includes comparing all possible build orientations to minimize voids in each layer, preventing void regions from being stacked in 3D, and avoiding creating an internal chimney. This approach is divided into three phases. Phase I is minimizing voids in each layer, phase II is identifying and managing voids between layers, and the third phase is comparing the total voids in all possible build orientations. Material extrusion processes, with a wide selection of nozzle sizes (0.4 mm to 21 mm), are considered suitable candidates for this solution. To carry out this study, a literature review was performed to understand the influence of the build parameters. Then, an analysis of valid parameter settings to be targeted was performed on a commercial system. The mathematical model is established based on the component geometry and the available build options for a given machine-material configuration. A C++ program has been developed to select a set of standard (available) toolpath parameters to determine the optimal output process variables (bead width, raster angle, and the overlap percentage), managing voids between layers, and compare total voids in all possible build orientations. Case studies are presented to show the merits of this approach. It is found that the entire void area is significantly reduced (~7%) with the phase I, by 5% with the second phase, at least 11% with phase III

Medialness and the Perception of Visual Art

In this article we explore the practical use of medialness informed by perception studies as a representation and processing layer for describing a class of works of visual art. Our focus is towards the description of 2D objects in visual art, such as found in drawings, paintings, calligraphy, graffiti writing, where approximate boundaries or lines delimit regions associated to recognizable objects or their constitutive parts. We motivate this exploration on the one hand by considering how ideas emerging from the visual arts, cartoon animation and general drawing practice point towards the likely importance of medialness in guiding the interaction of the traditionally trained artist with the artifact. On the other hand, we also consider recent studies and results in cognitive science which point in similar directions in emphasizing the likely importance of medialness, an extension of the abstract mathematical representation known as ‘medial axis’ or ‘Voronoi graphs’, as a core feature used by humans in perceiving shapes in static or dynamic scenarios.We illustrate the use of medialness in computations performed with finished artworks as well as artworks in the process of being created, modified, or evolved through iterations. Such computations may be used to guide an artificial arm in duplicating the human creative performance or used to study in greater depth the finished artworks. Our implementations represent a prototyping of such applications of computing to art analysis and creation and remain exploratory. Our method also provides a possible framework to compare similar artworks or to study iterations in the process of producing a final preferred depiction, as selected by the artist

Statistical shape analysis for bio-structures : local shape modelling, techniques and applications

A Statistical Shape Model (SSM) is a statistical representation of a shape obtained from data to study variation in shapes. Work on shape modelling is constrained by many unsolved problems, for instance, difficulties in modelling local versus global variation. SSM have been successfully applied in medical image applications such as the analysis of brain anatomy. Since brain structure is so complex and varies across subjects, methods to identify morphological variability can be useful for diagnosis and treatment. The main objective of this research is to generate and develop a statistical shape model to analyse local variation in shapes. Within this particular context, this work addresses the question of what are the local elements that need to be identified for effective shape analysis. Here, the proposed method is based on a Point Distribution Model and uses a combination of other well known techniques: Fractal analysis; Markov Chain Monte Carlo methods; and the Curvature Scale Space representation for the problem of contour localisation. Similarly, Diffusion Maps are employed as a spectral shape clustering tool to identify sets of local partitions useful in the shape analysis. Additionally, a novel Hierarchical Shape Analysis method based on the Gaussian and Laplacian pyramids is explained and used to compare the featured Local Shape Model. Experimental results on a number of real contours such as animal, leaf and brain white matter outlines have been shown to demonstrate the effectiveness of the proposed model. These results show that local shape models are efficient in modelling the statistical variation of shape of biological structures. Particularly, the development of this model provides an approach to the analysis of brain images and brain morphometrics. Likewise, the model can be adapted to the problem of content based image retrieval, where global and local shape similarity needs to be measured

Geometric, topological and semantic analysis of multi-building floor plan data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2006.Includes bibliographical references (leaves 65-67).Generating a comprehensive model of a university campus or other large urban space is a challenging undertaking due to the size, geometric complexity, and levels of rich semantic information contained in inhabited environments. This thesis presents a practical approach to constructing topological models of large environments from labeled floor plan geometry. An exhaustive classification of adjacency types is provided for a university infrastructure including roads, walkways, green-space, and the detailed interior spaces of campus buildings. The system models geospatial features for over 160 buildings within the MIT campus, consisting of more than 800 individual floors, and approximately 36,000 spaces spanning indoor and outdoor terrain. The main motivation is to develop an intuitive, human-centered approach to navigation systems. An application is presented for generating efficient routes between locations on MIT's campus with coverage of both interior and exterior environments. A second application, the MIT WikiMap, aims to generate a more expressive record of the environment by drawing from the knowledge of its inhabitants. The WikiMap provides an interface for collaborative tagging of geographical locations on the MIT campus, designed for interfacing with users to collect semantic data.by Emily J Whiting.S.M

Numerical study and optimization of a GT car Rear-Wing aerodynamics

The same principle that allows an airplane to rise off the ground by creating lift from its wings is used upside-down to generate the downforce that pushes a race car against the surface of the track. This effect is sometimes referred to as "aerodynamic grip" and is distinguished from "mechanical grip," which is dependent on the car mass distribution, tyre compunds and suspension characteristics. The creation of downforce by passive devices can only be achieved at the cost of increased aerodynamic drag (or friction), and the optimum setup is almost always a compromise between the two