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Computation -friendly shape grammars with application to determining the interior layout of buildings from image data.

机译:计算友好型语法,可用于根据图像数据确定建筑物的内部布局。

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A shape grammar is a formalism that has been widely applied, in many different fields, to analyzing designs. Computer implementation of a shape grammar interpreter is vital to both research and application. However, implementing a shape grammar interpreter is hard, especially for parametric shapes defined by open terms.;This dissertation explores the problem of implementing a shape grammar interpreter, which arose in the context of the AutoPILOT project, in which we were seeking an algorithm to determine the interior layout of a building given an input of building features and a shape grammar describing the building style. A general approach was adopted based on the fact that when applied exhaustively, a shape grammar can generate, as a tree, the entire layout space of the building style. The approach essentially requires a parametric shape grammar interpreter that caters to a variety of building types.;As extensions to the fact that shape grammars can simulate any Turing machine, three corollaries are found that significantly impact the implementation of a shape grammar interpreter. They are the following: a shape grammar may not ha the language space of a shape grammar may be exponentially large; and parsing of a configuration against a shape grammar is generally unsolvable. The problem of interpreting a general parametric shape grammar is thus in general intractable; even parametric subshape recognition of two-dimensional, rectilinear shapes may require a high-degree polynomial time.;In reality, there are distinct but large classes of shape grammars, with differing underlying characteristics, for which interpreters are known to be computationally tractable. In this dissertation, I present a practical, 'general' paradigm for ensuring the tractability of designed shape grammars and implementing such shape grammars.;Even these tractable shape grammars may significantly differ from one another. A further way of classifying these tractable shape grammars, optimally in my belief, is by the types of data structure capable of carrying out their rule application. There are, of course, other factors that influence the computation of shape grammars; these include the description language and all adopted underlying manipulations. As a consequence, the paradigm is augmented so that every interpreter is supported by an application programming interface-wise (API-wise) framework, which comprises an underlying data structure, basic manipulation algorithms, and a description meta-language. The paradigm specifies an overall framework comprising a series of sub-frameworks. The overall framework is capable of ensuring the computation for a specified shape grammar interpreter. Shape grammars, which follow such a framework, are termed as computation-friendly. .;The concept of the overall framework is detailed by examining three sub-frameworks. These include one over 2D rectangular shapes (Rectangular sub-framework), one over 2D polygonal shapes (Polygonal sub-framework), and one for shapes describable by a graph structure (Graph sub-framework). The issue of how to develop a computation-friendly shape grammar is explained and illustrated by using the Baltimore rowhouse grammar as the exemplar.;The rectangular sub-framework, which has direct application to the AutoPILOT project, is examined in detail. This includes an investigation of estimating an initial interior layout from the feature input by constraints solution, and the application of spatial constraints from an estimated initial layout to prune the layout tree and 'fix' the open terms of the intermediate configurations. The building feature input for the AutoPILOT project is typically difficult to obtain. The technical feasibility of automatically extracting building features from image data is examined by comparing two pipelines, an ideal pipeline and a realistic pipeline..;In summary, in this dissertation, I develop a general approach for determining building interior layouts from exterior features with the aid of shape grammars. Central to the general approach, issues of implementing a shape grammars interpreter are formally investigated by complexity analysis. Subsequently, a practical 'general' paradigm is developed and demonstrated by sub-framework examples. The paradigm facilitates the development of a practical shape grammar interpreter and is readily extensible to future development.
机译:形状语法是一种形式主义,已在许多不同领域广泛应用于分析设计。形状语法解释器的计算机实现对于研究和应用都至关重要。但是,实现形状语法解释器很困难,尤其是对于由开放术语定义的参数形状而言。本论文探讨了实现形状语法解释器的问题,该问题是在AutoPILOT项目的背景下提出的,我们正在寻求一种算法来解决这一问题。输入建筑物特征和描述建筑物样式的形状语法,即可确定建筑物的内部布局。基于以下事实,采用了一种通用方法:形状语法可以穷尽地应用,可以将建筑物样式的整个布局空间生成为树。该方法本质上需要满足各种建筑物类型的参数化形状语法解释器。作为对形状语法可以模拟任何图灵机的事实的扩展,发现了三个推论,它们对形状语法解释器的实现产生了重大影响。它们是:形状语法可能不会停止;形状语法的语言空间可能成倍增大;而针对形状语法的配置解析通常是无法解决的。因此,一般参数形语法的解释问题通常是棘手的。即使是二维直线形状的参数子形状识别也可能需要高次多项式时间。;实际上,存在许多不同但形状特征丰富的形状语法,它们具有不同的基本特征,众所周知,这些解释器在计算上是易于处理的。在本文中,我提出了一种实用的“通用”范式,以确保设计形状语法的可伸缩性并实现这种形状语法。即使这些易处理的形状语法也可能存在显着差异。我认为,对这些易处理的形状语法进行分类的另一种最佳方法是根据能够执行其规则应用程序的数据结构类型。当然,还有其他因素会影响形状语法的计算。这些包括描述语言和所有采用的基本操作。结果,范式得到了扩展,从而使每个解释器都得到了应用程序接口(API)框架的支持,该框架包括基础数据结构,基本操作算法和描述元语言。该范式指定了包括一系列子框架的整体框架。整个框架能够确保指定形状语法解释器的计算。遵循这种框架的形状语法被称为对计算友好的。通过检查三个子框架详细介绍了整个框架的概念。其中包括一种以上的2D矩形形状(“矩形”子框架),一种以上的2D多边形形状(“多边形”子框架),以及一种用于通过图形结构描述的形状(“图形”子框架)。以巴尔的摩排屋文法为例,解释和说明了如何开发计算友好的形状文法。详细研究了直接应用于AutoPILOT项目的矩形子框架。这包括对通过约束解决方案从要素输入中估计初始内部布局进行调查的研究,以及从估计的初始布局中应用空间约束以修剪布局树并“固定”中间配置的开放条件的调查。通常很难获得AutoPILOT项目的建筑特征输入。通过比较理想的管道和真实的管道这两个管道,检验了从图像数据中自动提取建筑特征的技术可行性。总而言之,在本文中,我开发了一种从外部特征确定建筑物内部布局的通用方法。形状语法的帮助。对于通用方法的核心,通过复杂度分析来正式研究实现形状语法解释器的问题。随后,开发了一种实用的“一般”范例,并通过子框架示例进行了演示。该范例促进了实用形状语法解释器的开发,并且很容易扩展到将来的开发中。

著录项

  • 作者

    Yue, Kui.;

  • 作者单位

    Carnegie Mellon University.;

  • 授予单位 Carnegie Mellon University.;
  • 学科 Design and Decorative Arts.;Information Technology.;Artificial Intelligence.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 202 p.
  • 总页数 202
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:05

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