3D CAD model retrieval based on the softassign quadratic assignment algorithm

A retrieval method for 3D CAD models based on the softassign quadratic assignment algorithm is presented in this paper. Firstly, retrieval models and target models are expressed as face adjacency graphs (FAGs) and thus 3D CAD model retrieval is turned to a graph matching problem. Secondly, vertex and edge compatibility matrices between the FAGs of a retrieval model and a target model are calculated. Then, an optimization objective function is created from compatibility matrices of a retrieval model and a target model, which serves as the similar metric for choosing vertex mapping matrix M of two models. Finally, the softassign quadratic assignment algorithm is introduced to find the optimal vertex mapping matrix M. Experimental results have shown that the proposed method supports 3D CAD model retrieval, and it is promising to meet the requirement of engineering applications.     

3D CAD model matching from 2D local invariant features

The matching of particular types of CAD models to existing physical models can provide invaluable support to the process of CAD design and reuse. To meet the demand for fast and robust algorithms to detect predefined models in database, an local invariant model matching approach is proposed in this paper. It first maps the 3D CAD model to 2D principal image plane by its first two principal components, and then finds affine invariant key points in the 2D image. The CAD model matching problem is implemented as key points matching. Experimental results show the proposed 3D model retrieval method performs fairly well in retrieving similar models from a database of 3D CAD models.     

三维CAD曲面模型距离-曲率形状分布检索算法

产品三维CAD模型检索对实现产品设计信息的有效重用具有重要意义和作用.针对在工程应用中存在大量含有曲面的产品,提出一种基于距离-曲率形状分布的三维CAD曲面模型检索算法.首先在模型表面随机取点,计算出所取点的曲率以及该点到模型质心的距离;然后以模型质心为球心,统计处在不同半径球壳间所取随机点的曲率分布,分别以球壳半径和曲率为坐标轴构建距离-曲率平面网格,并统计每个网格中随机点出现的频次,从而形成距离-曲率矩阵;最后利用特定的规则计算矩阵的相似值,用该值衡量2个模型的相似程度,实现模型的相似性检索.实验结果表明,文中算法的检索性能比传统的形状分布算法有较大提高,尤其适用于自由曲面模型的检索.     

Design reuse oriented partial retrieval of CAD models

As a huge number of 3D CAD models is generated each year, retrieval of 3D CAD models is becoming more and more important for achieving design reuse. However, the existing methods for partial retrieval of 3D CAD models are very few and far from the requirements of design reuse. In this paper, we present an approach to partial retrieval of 3D CAD models for design reuse. The criteria for determining whether a subpart of 3D CAD models is reusable for design is defined first. Based on the criteria defined, all the design reusable subparts involved in the 3D CAD models in the library are automatically extracted and stored in the library as reference models. Moreover, each design reusable subpart in the library is represented by all its local matching regions in a hierarchical way so as to support multi-mode partial retrieval. In our approach, three partial retrieval modes including normal retrieval, exact retrieval and relaxed retrieval are defined to meet various partial retrieval requirements of design reuse such as the incomplete and vague queries during the early design stage. And the multi-mode partial retrieval is achieved by performing multi-mode matching and similarity assessment between the query and the design reusable subparts in the library indexed by bitmap. Experimental results are presented to demonstrate the effectiveness of the approach.     

Manipulation of CAD surface models with haptics based on shape control functions

With traditional two-dimensional based interfaces, many CAD surface models are difficult to design and edit due to their 3D nature. This paper discusses a technique for the deformation of CAD surface models with haptic interaction based on shape control functions. With the technique, designers can use a haptic interface to directly touch a native B-rep CAD model, and deform it in real-time by pushing, pulling and dragging its surfaces in a natural 3D environment. The deformation is governed by shape control functions. By using the shape functions, designers can specify the area of deformation, and also have greater controls on the shape of deformation. This technique is numerically efficient, and can deform complex surface models involving several thousand control points in real-time. The haptic-based deforming approach gives designers greater flexibility for the manipulation of complex CAD surfaces.     

A deep learning approach to the classification of 3D CAD models简

Model classification is essential to the management and reuse of 3D CAD models. Manual model classification is laborious and error prone. At the same time, the automatic classification methods are scarce due to the intrinsic complexity of 3D CAD models. In this paper, we propose an automatic 3D CAD model classification approach based on deep neural networks. According to prior knowledge of the CAD domain, features are selected and extracted from 3D CAD models first, and then pre-processed as high dimensional input vectors for category recognition. By analogy with the thinking process of engineers, a deep neural network classifier for 3D CAD models is constructed with the aid of deep learning techniques. To obtain an optimal solution, multiple strategies are appropriately chosen and applied in the training phase, which makes our classifier achieve better per-formance. We demonstrate the efficiency and effectiveness of our approach through experiments on 3D CAD model datasets.     

Topology based 2D engineering drawing and 3D model matching for process plant

Process plant models mainly include 3D models and 2D engineering drawings. Matching calculation between these CAD models has wide applicability in model consistency check and retrieval. In process plant, engineering design standards make 2D engineering drawing and 3D model differ in geometry, proportion and structure, leading to the inapplicability of current shape-feature based matching approaches. Since connection relationships between components are the core of a process plant, a topology based algorithm is proposed. Firstly, by exploiting components as vertices and relationships as edges, both 2D engineering drawing and 3D model are preprocessed into graph structures. Then each model’s relationship types are extracted from the graph. Finally, regarding the extracted relationship types as primary feature, feature similarity is calculated to measure the matching degree between their corresponding models. The proposed algorithm is geometric deformation invariant. Experiments with industrial applications are presented, which demonstrates the effectiveness and feasibility of the proposed algorithm.     

Robust uniform triangulation algorithm for computer aided design

This paper presents a new robust uniform triangulation algorithm that can be used in CAD/CAM systems to generate and visualize geometry of 3D models. Typically, in CAD/CAM systems 3D geometry consists of 3D surfaces presented by the parametric equations (e.g. surface of revolution, NURBS surfaces) which are defined on a two dimensional domain. Conventional triangulation algorithms (e.g. ear clipping, Voronoi-Delaunay triangulation) do not provide desired quality and high level of accuracy (challenging tasks) for 3D geometry. The approach developed in this paper combines lattice tessellation and conventional triangulation techniques and allows CAD/CAM systems to obtain the required surface quality and accuracy. The algorithm uses a Cartesian lattice to divide the parametric domain into adjacent rectangular cells. These cells are used to generate polygons that are further triangulated to obtain accurate surface representation. The algorithm allows users to control the triangle distribution intensity by adjusting the lattice density. Once triangulated, the 3D model can be used not only for rendering but also in various manufacturing and design applications. The approach presented in this paper can be used to triangulate any parametric surface given in S(u,v) form, e.g. NURBS surfaces, surfaces of revolution, and produces good quality triangulation which can be used in CAD/CAM and computer graphics applications.     

基于网络本体语言的三维计算机辅助设计主模型相似性计算方法

为了提高三维计算机辅助设计(CAD)模型重用效率,针对当前三维模型检索系统中语义表达不足问题,提出了一种基于网络本体语言(OWL)表示模型语义的相似性计算方法。首先,将三维CAD产品主模型转化成以概念属性特征为基础语义对象的结构化表示模型;然后,从OWL表示模型中提取用于评价两个模型相似性的特征语义信息,构建可量化的相似元集,借助子图同构思想和Tversky算法给出了一种加权相似性计算方法;最后,通过实例验证了所提方法的有效性和可行性。实验的定量评价结果表明,该评价基准从对象本身转为两个对象特性的语义描述,能够客观反映两对比模型的相似程度。     

A diffusion wavelet approach for 3-D model matching

This paper proposes a new 3D shape retrieval approach based on diffusion wavelets which generalize wavelet analysis and associated signal processing techniques to functions on manifolds and graphs. Unlike current works on 3D matching, which are based either on the topological information of the model or its scatter point distribution information, this approach uses both information for more effective matching. Diffusion wavelets enable both global and local analyses on graphs, and can capture the topology of a surface with the diffusion map of its mesh representation. As a result, both multi-scale properties of the 3D geometric model and the topology among the meshes can be extracted for use in 3D geometric model retrieval. Tests using 3D benchmarks demonstrate that the approach based on diffusion wavelets is effective and performs better than those by spherical wavelet and spherical harmonics in 3D model matching.     

基于子图同构的三维CAD模型局部匹配

针对整体相似性检索算法无法实施精确的局部结构匹配的问题,提出一种基于子图同构的三维CAD模型局部结构匹配算法.该算法通过提取CAD模型的B-Rep信息,将其表示为以面作为节点的属性邻接图.在局部匹配过程中,用户输入的局部结构被表示成"子图".待匹配的整体CAD模型被表示成"大图";则在整体CAD模型中.检索局部结构的问题就被转换成在"大图"中寻找同构"子图"的问题.子图同构是NP完全问题,通过利用CAD模型的面特征将图顶点有效细分,并利用已匹配顶点之间的邻接关系动态裁剪搜索空间,实现了快速的同构匹配.实验结果表明,该算法能实现精确的局部结构匹配,并且检索效率能满足实际应用要求.     

3D head model retrieval in kernel feature space using HSOM

In this paper, we propose a novel 3D head model retrieval framework. Specifically, to facilitate better classification and retrieval, the original 3D head model representations are embedded into another kernel feature space in which kernel principal component analysis (kernel PCA) is then performed to search for the optimal basis representation. Based on the extracted nonlinear features, a hierarchical indexing structure for 3D model retrieval is constructed using the hierarchical self organizing map (HSOM). The proposed indexing structure clusters the database into a hierarchy so that head models are partitioned by coarse features initially and then by finer scale features at lower levels. The main motivation of adopting this approach is that subspace technique like kernel PCA provides an elegant mechanism to describe the 3D head models on multiple resolutions based on the choices for reconstruction error and the orthogonal property of the produced eigenvectors. To further enhance the performance, a fuzzy metric between the query and the feature vector associated with each node on the SOMs is adopted instead of the usual Euclidean metric. Only nodes that possess high fuzzy measure values will be considered further for retrieval. In this way, the fuzzy measure approach is able to pick up potential relevant models even though they may be distributed across a number of neighbouring nodes. In addition to model categorization, the topology-preserving property of HSOM also facilitates the exploration of the model database with the possibility for further knowledge discovery. The effectiveness of the proposed approach is verified by a set of simulation examples on a 3D head model database.     

Efficient data structures for model-based 3-D object recognitionand localization from range images

An effective method of surface characterization of 3D objects using surface curvature properties and an efficient approach to recognizing and localizing multiple 3D free-form objects (free-form object recognition and localization) are presented. The approach is surface based and is therefore not sensitive to noise and occlusion, forms hypothesis by local analysis of surface shapes, does not depend on the visibility of complete objects, and uses information from a CAD database in recognition and localization. A knowledge representation scheme for describing free-form surfaces is described. The data structure and procedures are well designed, so that the knowledge leads the system to intelligent behavior. Knowledge about surface shapes is abstracted from CAD models to direct the search in verification of vision hypotheses. The knowledge representation used eases processes of knowledge acquisition, information retrieval, modification of knowledge base, and reasoning for solution     

三维CAD模型检索综述

对三维CAD模型检索研究现状进行了深入和系统的综述。CAD模型检索可划分为两个层次:基于视觉相似性的三维CAD模型检索、面向语义与功能描述的三维CAD模型检索。分别分析了两种检索层次下CAD模型的检索方法。在此基础上总结了三维CAD模型检索评测基准库、评测方法等。最后展望了现有研究中的难点及进一步的研究方向。     

Shape differentiation of freeform surfaces using a similarity measure based on an integral of Gaussian curvature

Freeform surfaces are popularly used to design and model complex 3D objects. These 3D models are stored as computerized models in databases. To facilitate data retrieval and shape matching, a major challenge lies in defining and computing the level of similarity between two or more freeform surfaces. In order to explore the useful 3D information associated with the surfaces, an integrated approach based on the integral of Gaussian curvature is proposed to develop the measures of similarity of freeform surfaces. Specifically, the integral of Gaussian curvature is mapped into the 2D space, and a shape-based measure is developed using statistical methods to compute the level of similarity. For smooth surfaces, a fast approximation algorithm is developed to calculate the curvature of individual subregions. In cases where the target surface has a complex topological structure or a smooth surface is not available, the integral of Gaussian curvature for the discrete surface is first calculated at each vertex, followed by mapping onto a 2D spherical coordinate. The distance measure focuses on the local geometry, which is critical to investigate models with a certain level of resemblance such as products in a family. This proposed approach can be applied to surfaces under various transformations, as well as 3D data from various sources.     

一种基于拓扑连接图的三维模型检索方法

提出了一种基于分割技术的拓扑连接图构造方法。并用于三维模型检索．首先构造多层邻域计算用于度量每个三角片平坦度的信号值。根据这些信号值采用一种改进的分水岭方法把模型分割成不同的曲面片．然后利用这些曲面片之间的连接关系构造拓扑连接图．最后通过比较不同模型的拓扑连接图相似性来得到它们的匹配度。根据匹配度进行三维模型检索．