一個視覺物體或一個三維模型的骨架，是一種可以揭示該物體或模型的拓樸結構的呈現方式，因此骨架可以被應用在諸多場合當中，例如形狀分析和電腦動畫。近年來，有許多針對從一個物體當中抽取骨架的研究工作。然而，大多數的研究著重於完整和乾淨的資料（儘管這些研究當中，有一些有將缺失值考慮在內），但在實務上，我們經常要處理不完整和不潔淨的資料，就像資料裡面可能有缺失值和雜訊。在本論文中，我們研究雜訊處理，而且我們將焦點放在針對帶有雜訊的點雲資料進行前置處理，以便生成相應物體的骨架。在我們提出的方法當中，我們首先識別可能帶有雜訊的資料點，然後降低雜訊值的影響。為了識別雜訊，我們將監督式學習用在以密度和距離作為特徵的資料上。為了降低雜訊值的影響，我們採用三角形表面和投影。這個前置處理方法是有彈性的，因為它可以搭配任何能夠從點雲資料當中抽取出物體的骨架的工具。我們用數個三維模型和多種設定進行實驗，而結果顯示本論文所提出的前置處理方法的有效性。與未經處理的模型（也就是原始模型加上雜訊）相比，在從帶有雜訊的點雲資料當中產生物體的骨架之前，如果我們先使用本論文所提出的前置處理方法，那麼我們可以得到一個包含更多原來的物體的拓撲特徵的骨架。我們的貢獻如下：第一，我們展示了機器學習可以如何協助電腦圖學。第二、針對雜訊識別，我們提出使用距離和密度做為學習過程中要用的特徵。第三、我們提出使用三角表面和投影，以減少在做雜訊削減時所需要花費的時間。第四、本論文提出的方法可以用於改進三維掃描。 / The skeleton of a visual object or a 3D model is a representation that can reveal the topological structure of the object or the model, and therefore it can be used in various applications such as shape analysis and computer animation. Over the years there have been many studies working on the extraction of the skeleton of an object. However, most of those studies focused on complete and clean data (even though some of them took missing values into account), while in practice we often have to deal with incomplete and unclean data, just as there might be missing values and noise in data. In this thesis, we study noise handling, and we put our focus on preprocessing a noisy point cloud for the generation of the skeleton of the corresponding object. In the proposed approach, we first identify data points that might be noise and then lower the impact of the noisy values. For identifying noise, we use supervised learning on data whose features are density and distance. For lowering the impact of the noisy values, we use triangular surfaces and projection. The preprocessing method is flexible, because it can be used with any tool that can extract skeletons from point clouds. We conduct experiments with several 3D models and various settings, and the results show the effectiveness of the proposed preprocessing approach. Compared with the unprocessed model (which is the original model with the added noise), if we apply the proposed preprocessing approach to a noisy point cloud before using a tool to generate the skeleton, we can obtain a skeleton that contains more topological characteristics of the model. Our contributions are as follows: First, we show how machine learning can help computer graphics. Second, we propose to use distance and density as features in learning for noise identification. Third, we propose to use triangular surfaces and projection to save execution time in noise reduction. Fourth, the proposed approach could be used to improve 3D scanning.

Access to abstract permanently restricted to Ball State community only / Access to thesis permanently restricted to Ball State community only / School of Physical Education, Sport, and Exercise Science

No description available.

<p>Sea urchin larvae possess a beautiful, intricately patterned, calcium-carbonate skeleton. Formation of this complex structure results from two independent processes within the developing embryo: specification of the mesenchymal cells that produce the skeletal rods, and patterning inputs from the ectoderm, which secretes signals directing the growth and shape of the skeleton. To understand patterning of the skeleton therefore, the specification events behind these two processes must be understood separately, and then connected in order to understand how ectoderm signaling directs skeletal growth. While the former processes of mesenchyme specification and mineralization are under study elsewhere, the means by which ectodermal cues directing skeletal growth are activated and localized is not known. Using molecular genetics, including gene knock downs and mis-expression, as well as microsurgical manipulations of early cleavage embryos, I show how a previously undescribed territory within the ectoderm, the border ectoderm (BE) is specified with short range signaling inputs. Then, experiments show that the BE provides signals that initiate, and contribute to the propagation of skeletogenesis. From this dataset, and from biological experiments I outline a model for how the BE patterns and contributes to the directed growth of the skeleton. I also discuss challenges to this model that need to be addressed in future research. In principle, the mechanism proposed herein depends on the integration of information from both the primary and secondary embryonic axes. It requires both short-range signaling by Wnt5 from the endoderm to establish the BE fate, and TGFß signaling from the oral and aboral ectoderm which subdivides the BE into four territories. These findings demonstrate that the short-range signaling cascade that subdivides the embryo into first mesoderm and then endoderm also specifies ectodermal fates. Ultimately, this research paves the way for understanding how the larval skeleton is patterned during embryogenesis and may provide a paradigm for understanding other, more complex, developmental problems.</p> / Dissertation

Thesis (Ph.D.) -- La Trobe University, 2006. / "A thesis submitted in total fulfilment of the requirements for the degree of Doctor of Philosophy, Dept. of Zoology, School of Life Sciences, La Trobe University". Research. Includes bibliographical references (p. 445-481). Also available via the World Wide Web.

Thesis (Ph. D.)--University of Oregon, 2008. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 281-287). Also available online in Scholars' Bank; and in ProQuest, free to University of Oregon users.

Thesis (M.S.)--University of Michigan, 1967.

Thesis (M.S.)--University of Michigan, 1967.

Thesis--University of Michigan. / Bibliography: p. 75-82.

Thesis (M.A.)--Texas State University--San Marcos, 2009. / Vita. Appendices: leaves 51-76. Includes bibliographical references (leaves 77-82). Also available on microfilm.