Hierarchical structure to winged-edge structure: a conversion algorithm

The winged-edge data structure is advantageous for traversing the topological graph of the boundary representation of a solid object. This paper presents an algorithm for converting hierarchical boundary representations into representations in the winged-edge data structure. As a result of the conversion, the adjacency relationships of geometric entities embedded in hierarchical boundary representations,-which may be evaluated through boundary evaluation on solid objects defined via Boolean set-operations, can be easily and efficiently accessed.     

Graph-based extraction of two-connected morphological features from boundary representations

In this paper a feature extraction technique to isolate two-connected features from a boundary model is discussed. The technique involves identification of faces with multiple edge loops and faces sharing multiple edges as candidates for entrance faces of such features. It is observed that the two-connected features constitute tri connected components in the edge-face graphs of the boundary models. Heuristics are used to enhance an algorithm to decompose the edge-face graph of a boundary representation into its triconnected components. Pros and cons of this method are compared with the classic graph theoretic algorithm used to obtain triconnected components from a graph.     

Generating compact representations of static scenes by means of 3D object hierarchies

This paper presents a new heuristic algorithm for computing a compact hierarchical representation of the objects contained in a 3D static scene. The algorithm first builds a fully-connected adjacency graph that keeps the costs of grouping the different pairs of objects of the scene. Afterward, the graph’s minimum spanning tree is computed and its edges sorted in ascending order according to their cost. Next, from that sorted list, a cost-based clustering technique is applied, thus generating new objects at a higher level in the hierarchy. A new object can be defined after merging two or more objects according to their corresponding linking costs. The algorithm starts over by generating a new adjacency graph from those new objects, along with the objects that could not be merged before. The iterative process is applied until an adjacency graph with a single object is obtained. The latter is the root of the hierarchical representation. Balance and coherence of the hierarchy, in which spatially close objects are also structurally close, is achieved by defining an appropriate cost function. The proposed technique is evaluated upon several 3D scenes and compared to a previous technique. In addition, the benefits of the proposed technique with respect to techniques based on octrees and kd-trees are analyzed in terms of a practical application.     

基于图像内容层次表征的遥感图像 分割方法

提出基于图像内容层次表征的高分辨率遥感图像快速多精度分割方法。首先根据初始分割结果建立区域邻接图(RAG),并将其定义为马尔可夫随机场(MRF);然后引入光谱、形状和边缘等图像特征进行层次合并,通过记录层次合并过程获得图像内容的层次表征;最后根据层次表征中不同层级对象之间的关系快速生成任意不同精度的分割结果,以满足不同应用的需求。利用QuickBird卫星图像进行实验和评价的结果表明,本文方法具有较高的精度和效率。     

Inductive hierarchical nonnegative graph embedding for “verb–object” image classification

Most existing image classification algorithms mainly focus on dealing with images with only “object” concepts. However, in real-world cases, a great variety of images contain “verb–object” concepts, rather than only “object” ones. The hierarchical structure embedded in these “verb–object” concepts can help to enhance classification. However, traditional feature representation methods cannot utilize it. To tackle this problem, we present in this paper a novel approach, called inductive hierarchical nonnegative graph embedding. By assuming that those “verb–object” concept images which share the same “object” part but different “verb” part have a specific hierarchical structure, we integrate this hierarchical structure into the nonnegative graph embedding technique, together with the definition of inductive matrix, to (1) conduct effective feature extraction from hierarchical structure, (2) easily transfer each new testing sample into its low-dimensional nonnegative representation, and (3) perform image classification of “verb–object” concept images. Extensive experiments compared with the state-of-the-art algorithms on nonnegative data factorization demonstrate the classification power of proposed approach on “verb–object” concept images classification.     

Using structured steiner trees for hierarchical global routing

The Steiner problem in a hierarchical graph model, the structured graph, is defined. The problem finds applications to hierarchical global routing. Properties of minimum-cost Steiner trees in structured graphs are investigated. A “top-down” approximate solution to the Steiner problem in structured graphs, called a top-down Steiner tree, is defined, and an algorithm is given to compute such solution. The top-down Steiner tree provides also an approximate solution to the Steiner problem in graphs admitting a structured representation. The properties of such solution are discussed and some experimental results on the quality of the approximation are presented. A reduction in time complexity is demonstrated with respect to both exact and heuristic algorithms applied to such graphs.     

A model-driven approach to semi-structured database design

Recently XML has become a standard for data representation and the preferred method of encoding structured data for exchange over the Internet. Moreover it is frequently used as a logical format to store structured and semi-structured data in databases. We propose a model-driven and configurable approach for modeling hierarchical XML data using object role modeling (ORM) as a flat conceptual model. First a non-hierarchical conceptual schema of the problem domain is built using ORM and then different hierarchical views of the conceptual schema or parts of it are specified by the designer using transformation rules. A hierarchical modeling notation called H-ORM is proposed to show these hierarchical views and model more complex semi-structured data constructs and constraints. We also propose an algorithm to map hierarchical H-ORM views to XML schema language.     

Multi-scale 2D tracking of articulated objects using hierarchical spring systems

This paper presents a flexible framework to build a target-specific, part-based representation for arbitrary articulated or rigid objects. The aim is to successfully track the target object in 2D, through multiple scales and occlusions. This is realized by employing a hierarchical, iterative optimization process on the proposed representation of structure and appearance. Therefore, each rigid part of an object is described by a hierarchical spring system represented by an attributed graph pyramid. Hierarchical spring systems encode the spatial relationships of the features (attributes of the graph pyramid) describing the parts and enforce them by spring-like behavior during tracking. Articulation points connecting the parts of the object allow to transfer position information from reliable to ambiguous parts. Tracking is done in an iterative process by combining the hypotheses of simple trackers with the hypotheses extracted from the hierarchical spring systems.     

Reprint of: Multi-scale 2D tracking of articulated objects using hierarchical spring systems

This paper presents a flexible framework to build a target-specific, part-based representation for arbitrary articulated or rigid objects. The aim is to successfully track the target object in 2D, through multiple scales and occlusions. This is realized by employing a hierarchical, iterative optimization process on the proposed representation of structure and appearance. Therefore, each rigid part of an object is described by a hierarchical spring system represented by an attributed graph pyramid. Hierarchical spring systems encode the spatial relationships of the features (attributes of the graph pyramid) describing the parts and enforce them by spring-like behavior during tracking. Articulation points connecting the parts of the object allow to transfer position information from reliable to ambiguous parts. Tracking is done in an iterative process by combining the hypotheses of simple trackers with the hypotheses extracted from the hierarchical spring systems.     

A pyramidal data structure for triangle-based surface description

A hierarchical model for approximating 2-1/2-dimensional surfaces is described. This model, called a Delaunay pyramid, is a method for compression of spatial data and representation of a surface at successively finer levels of detail. A Delaunay pyramid is based on a sequence of Delaunay triangulations of suitably defined subsets of the set of data points. A triangle-oriented encoding structure for a Delaunay pyramid is presented, and its storage complexity is evaluated. An algorithm for constructing a Delaunay pyramid is described, and a method for solving the point location and evaluation on such a model is discussed     

Representing dimensions, tolerances, and features in MCAE systems

A method is presented for explicitly representing dimensions, tolerances, and geometric features in solid models. The method combines CSG and boundary representations in a graph structure called an object graph. Dimensions are represented by a relative position operator. The method can automatically translate changes in dimensional values into corresponding changes in geometry and topology. The representation provides an important foundation for higher-level application programs to automate tolerance analysis and synthesis. The implementation of a prototype interactive polyhedral modeler based on this representation is presented     

A hierarchical representation for heterogeneous object modeling

A hierarchical representation for heterogeneous object modeling is presented in this paper. To model a heterogeneous object, Boundary representation is used for geometry representation, and a novel Heterogeneous Feature Tree (HFT) structure is proposed to represent the material distributions. HFT structure hierarchically organizes the material variation dependency relationships and is intuitive in modeling different types of material gradations. Based on the HFT structure, a recursive material evaluation algorithm is proposed to dynamically evaluate the material compositions at a specific location. Such a hierarchical representation guarantees complex material gradations and the user's design intent can be intuitively represented. Example heterogeneous objects modeled with this scheme are provided and potential applications are discussed.     

A Model for Representing Programs Using Hierarchical Graphs

In this paper a hierarchical graph model for programs based on the concepts of recursive graphs (RG's) and Codd relations is presented. The purpose of the model is to clearly represent the structure of a program implemented in a structured language, such as Pascal, Algol, or PL/1, so that the program can be analyzed and modifications to the program can be clearly specified. The model uses an RG representation for the control flow and the data flow with an equivalent relational representation. It also has a relational representation for the objects defmed within the program. The various aspects of the model are illustrated using Pascal constructs and a model for an example Pascal program is given.     

求解布局模型的并行矩阵算法研究

布局设计通常要建立抽象状态空间模型。求解布局模型，实现从模型状态到坐标图的转化，是计算机辅助布局设计的重要研究内容之一。本文在简要介绍一种层次布局模型ＨＬＭ１的基础上，引入了模型的解的概念；研究了ＨＬＭ１的子模型－层次约束图解的存在条件；提出了求解层次约束图，实现从模型到坐标图转化以及检测约束矛盾的一种并行矩阵算法，并给出了一个计算实例。     

Two-manifold cell-decomposition of r-sets.

This paper discusses the relationships studied between manifold solids and r-sets by defining an r-set as a decomposition in two-manifold cells. This decomposition is represented as a graph (Two-manifold Cell Decomposition graph TCD) in which each node corresponds to a 2 manifold component of the regular set, while each arc or hyperarc defines a non-manifold adjacency between components. The TCD model and data structure encoding it were designed in order to be compatible with a traditional boundary architecture.     

基于骨架层次分解的目标的图表示

基于骨架的目标表示技术是模式识别和计算机视觉的重要研究内容,近年来人们提出了许多骨架化算法,但是有关利用骨架信息表示并识别目标的研究还非常有限。Ablameyko等1996年提出了通过分解由距离标号的骨架为有意义的结构基元从而获得目标的层次结构图的方法。该图可以准确地刻画基元之间的拓扑关系,但是它对于骨架中的噪声比较敏感。主要表现为噪声基元破坏其它基元的完整性和图的稳定性。该文采用将分支编组为分支链以及构造多尺度结构图的改进策略来克服这些缺点,最终获得了目标的节点数更小、节点显著度更高、节点间连接关系更稳定的多尺度图,从而显著地提高后续利用不精确图匹配技术进行目标识别的效率。这项技术已经被应用于一个基于形状特征的图像数据库检索系统中。