多个剖切平面下剖视图的生成

利用AME提供的应用程序接口(API),对AME模块中的功能进行了改进,新的剖面命令可以得到任意多个剖切平面下三维实体的剖视图,并且突破了AME剖面只能是全剖视图的限制。     

Solid Edge工程图设计中的两个问题

一、隐藏视图 在Ｓｏｌｉｄ Ｅｄｇｅ的工程图环境设计三维模型（＊·ｐａｒ,＊·psm,＊．ａｓｍ）的工程图时,有时需要隐藏整个或部分视图。如要生成剖视图,必须先生成一个投影视图,在上面添加剖面分割线,然后再生成剖视图。有时我们只需要剖视图,而不需要与之关联的投影视图。但如果直接删除该投影视图,与之关联的剖视图也就会消失。又如要在一个投影视图上作一个局部剖,则必须隐藏部分线条,这时就必须要用到隐藏视图的技术。归纳起来,隐藏视图的方法主要有以下几种。 第一种方法是通过右键快捷菜单先把要保留的剖视图转换为工…     

Autodesk Inventor工程图的创建及使用(二)

一、剖视图 1.剖视图的创建 单击"剖视图"按钮并选择一个视图,之后在图形区域单击以设置剖切线的起点,并以同样的方式确定其余点以完成剖切路径线的绘制,最后在右键菜单中选择"继续"后,将弹出如图1所示的界面.     

三维重建中的剖视图处理

剖视图处理能够有助于更好地理解视图,提高三维重建的效率。基于对剖视图自身特点的分析,提出了三维重建中对剖视图的处理算法,即通过剖视图信息的智能提取生成基元体,将基元体同由视图轮廓生成的参照体进行布尔运算,从而得到最终的目标体。算法能够处理包括全剖视图、半剖视图以及平行剖视图在内的剖视图,最后给出了应用算例以验证算法的可行性。     

三维冷冲模设计的剖切图自动生成

工程图样是工程技术部门表达和交流技术思想的重要工具，剖视图是其重要组成部分。目前许多商业化的图形软件包已经具备了三维实体向二维转换的通用工具，但是在实际应用中并不是十分有效。根据零件的孔、槽等剖切特征，提出基于优先度和基于图遍历的两种自动搜索关键特征产生剖切线的算法，并分别结合实例进行了比较。结果表明，这两种算法在基于模板的冷冲模CAD系统的实际应用中是理想、可靠的。     

在AutoCAD2000中用三维模型生成三视图的技巧

本文主要介绍利用AutoCAD2000的图纸布局功能,利用用户已经绘制的三维模型生成三视图。当切换到图纸空间后,AutoCAD在屏幕上显示一张二维图纸,并自动创建一个显示三维模型的浮动窗口,可根据三维模型轻易地创建多种形式的布局。用户也可以调整窗口视点以获得所需的主视图,然后再用SOLVIEW命令生成其他视图,如正交视图、剖视图、斜视图等。下面将通过实例来介绍由三维模型生成三视图的技巧,并着重介绍标准的主视图、左视图、俯视图、剖视图的生成方法。一、利用三维模型创建各视图的窗口 1. 主视图窗口的创建首先打开已经绘制好…     

AutoCAD环境下基于三维模型的二维视图创建方法

对AutoCAD环境下根据三维模型创建二维平面视图,尤其是剖视图的方法进行了分析探讨。方法之一是将三维模型上平行于投影面的表面或表面的轮廓线经复制、编辑、补线等操作,即得到对应于该投影面的视图、剖视图。方法之二是利用截面命令（section）或截面平面命令（sectionplane）创建穿过三维模型的横截面,再经编辑、补线等操作,将该横截面创建成所需的剖视图。     

基于复杂工程图的三维造型草图生成算法

提出一种基于复杂工程图的快速三维草图生成算法,以及一种视图选择分 割子算法。该子算法不仅结合了主流三种分割算法的优点,对视图分割具有选择性和次序性, 而且最多四次分割就能达到对复杂工程图彻底分割的目的。改进的角度判别法进一步提高了 算法的整体效率。最终通过实例验证,可处理现有CAD 软件对二维图的导入,提高了三维 几何造型的效率。     

AutoCAD三维图形剖切功能的实现

本文介绍了对ＡｕｔｏＣＡＤ三维图形实现剖切功能的方法，并编制了相应的实用软件。在ＡｕｔｏＣＡＤ系统下，调入被剖切后的图形数据，就可由Ｖｐｏｉｎｔ和Ｄｖｉｅｗ命令分别生成轴测剖视图和透视剖视图。从而为利用ＡｕｔｏＣＡＤ三维造型提供了强有力的辅助手段。     

一种二维工程图向三维模型的尺寸映射算法

针对当前制造型企业内部存在二维工程图和三维CAD模型之间的数据共享问题,提出一种基于图匹配的二维工程图向三维CAD模型的尺寸映射算法,将二维工程图中的尺寸信息直接映射到对应的三维CAD模型上。首先将三维模型进行投影得到投影视图,然后将投影视图和二维工程图转化为一种空间关系图,对两个空间关系图进行图匹配,找出图元间的映射关系,并且利用工程图中尺寸标注的特点对算法进行改进,提高算法效率和可靠性。实验结果表明,该算法可以很好的实现二维工程图向三维CAD模型的尺寸映射。     

基于形体逼近的三维重建算法

该文提出一种新的由三视图重建三维实体的算法,能扩展自顶向下的三维重建算法的形体覆盖域,并在Auto-CAD平台上验证了算法的有效性。算法的主要步骤是首先用平扫-旋转-求交的实体运算法则构造出与所求实体形状相近的实体———第1参照体,再模拟人脑的识图过程:把第1参照体的三视图与初始三视图对比,根据两者之间的差别构造出差异体,再从第1参照体中逐一减去差异体,得到第2参照体、第3参照体......最后得到所求的实体。     

多视点识别三维运动目标新方法

本文讨论了从多视点识别三维运动目标问题．该方案基于对连续输入的二维图像聚类,构成 三维目标的特征视图和转移矩阵,利用极 对数坐标变换（LPM）和离散付立叶变换（DFT） 提取出与目标二维特征视图的位置、比例和旋转无关的特征向量．ART-2模型作为目标特征 信息的存储器和分类器．实验中对ART-2神经网络进行了改进,取得了满意的结果．     

3D Object retrieval based on viewpoint segmentation

In the last decades, extensive efforts have been dedicated to develop better 3D object retrieval methods. View-based methods have attracted a significant amount of attention, not only because of their state-of-the-art performance, but also they merely require some of a 3D object’s 2D view images. However, most recent approaches only deal with the images’ content difference without the discrepancy of view relative positions. In this paper, we propose a normal method for view segmentation, based on Markov random field (MRF) model, which consider not only the difference between the content of views but also the relative locations. Each view is obtained by projecting at certain viewpoints and angels, therefore, these locations can be applied to depict each view, with content of views. We use the MRF to implement view segmentation and choose the representative views. Finally, we present a framework based on the proposed view segmentation method for 3D object retrieval and the experimental results demonstrate that the proposed method can achieve better retrieval effectiveness than state-of-the-art methods under several standard evaluation measures.     

Constructing a wire-frame from views on arbitrary view planes for objects with conic sections inclined to all view planes

A new and efficient approach to construct a 3D wire-frame of an object from its orthographic projections is described. The input projections can be two or more and can include regular and complete auxiliary views. Each view may contain linear, circular and other conic sections. The output is a 3D wire-frame that is consistent with the input views.The approach can handle auxiliary views containing curved edges. This generality derives from a new technique to construct 3D vertices from the input 2D vertices (as opposed to matching coordinates that is prevalent in current art). 3D vertices are constructed by projecting the 2D vertices in a pair of views on the common line of the two views. The construction of 3D edges also does not require the addition of silhouette and tangential vertices and subsequently splitting edges in the views. The concepts of complete edges and n-tuples are introduced to obviate this need. Entities corresponding to the 3D edge in each view are first identified and the 3D edges are then constructed from the information available with the matching 2D edges. This allows the algorithm to handle conic sections that are not parallel to any of the viewing directions. The localization of effort in constructing 3D edges is the source of efficiency of the construction algorithm as it does not process all potential 3D edges.Working of the algorithm on typical drawings is illustrated.     

Genetic object recognition using combinations of views

Investigates the application of genetic algorithms (GAs) for recognizing real 2D or 3D objects from 2D intensity images, assuming that the viewpoint is arbitrary. Our approach is model-based (i.e. we assume a pre-defined set of models), while our recognition strategy relies on the theory of algebraic functions of views. According to this theory, the variety of 2D views depicting an object can be expressed as a combination of a small number of 2D views of the object. This implies a simple and powerful strategy for object recognition: novel 2D views of an object (2D or 3D) can be recognized by simply matching them to combinations of known 2D views of the object. In other words, objects in a scene are recognized by "predicting" their appearance through the combination of known views of the objects. This is an important idea, which is also supported by psychophysical findings indicating that the human visual system works in a similar way. The main difficulty in implementing this idea is determining the parameters of the combination of views. This problem can be solved either in the space of feature matches among the views ("image space") or the space of parameters ("transformation space"). In general, both of these spaces are very large, making the search very time-consuming. In this paper, we propose using GAs to search these spaces efficiently. To improve the efficiency of genetic searching in the transformation space, we use singular value decomposition and interval arithmetic to restrict the genetic search to the most feasible regions of the transformation space. The effectiveness of the GA approaches is shown on a set of increasingly complex real scenes where exact and near-exact matches are found reliably and quickly     

A Survey of 3D Solid Reconstruction from 2D Projection Line Drawings

The reconstruction of a 3D object from its 2D projection(s) and its corresponding problem of 3D object recognition are two of the important research areas in the field of computer vision and artificial intelligence. Reconstruction involves determining the geometric and topological relationship of an object's atomic parts whereas recognition involves identifying an object by some form of template matching. Nagendra and Gujar¹ gave a survey of several papers on reconstruction of 3D object from its 2D views. In this paper we present a taxonomy of 3D object reconstruction from 2D projection line drawings. We base the classification on the number of 2D views of the 3D solid object, the degree of user interaction necessary for correct reconstruction, and the internal representation used in the reconstruction process. We discuss the basic issues associated with this problem, review the relevant literature and present topics for future research.     

基于联合特征匹配的多视角三维重建方法

本研究提出了一种基于角点与直线联合特征的三阶段匹配算法,依次经过相关匹配、松弛迭代匹配和最小平方中值法匹配三个步骤,并与此同时加入限定图像匹配区域、添加手工匹配点对以及局部直线匹配三个人机交互环节,将局部坐标系中得到的数据点进行三维数据融合到一个坐标系中,能较好解决视差不连续区域和遮挡区域的误匹配问题.实验证明该算法具有良好的运行效率和稳定性,能够对非平面物体进行精确三维重建并实现多视角显示.     

Shape recovery from turntable sequence using rim reconstruction

This paper makes use of both feature points and silhouettes to deliver fast 3D shape recovery. The algorithm exploits object silhouettes in two views to establish a 3D rim curve, which is defined with respect to the two frontier points arising from two views. The images of this 3D rim curve in the two views are matched using cross-correlation technique. A 3D planar rim curve is then reconstructed using point-based reconstruction method. A set of 3D rim curves enclosing the object can be obtained from an image sequence captured under circular motion. Silhouettes are further utilized to check for mismatched rim points. The proposed method solves the problem of reconstruction of concave object surface, which is usually left unresolved in general silhouette-based reconstruction methods. In addition, the property of the reconstructed 3D rim curves allows fast surface extraction. Experimental results with real data are presented.     

Tracking and Motion Estimation of the Articulated Object: a Hierarchical Kalman Filter Approach

Real-time motion capture plays a very important role in various applications, such as 3D interface for virtual reality systems, digital puppetry, and real-time character animation. In this paper we challenge the problem of estimating and recognizing the motion of articulated objects using theoptical motion capturetechnique. In addition, we present an effective method to control the articulated human figure in realtime.The heart of this problem is the estimation of 3D motion and posture of an articulated, volumetric object using feature points from a sequence of multiple perspective views. Under some moderate assumptions such as smooth motion and known initial posture, we develop a model-based technique for the recovery of the 3D location and motion of a rigid object using a variation of Kalman filter. The posture of the 3D volumatric model is updated by the 2D image flow of the feature points for all views. Two novel concepts – the hierarchical Kalman filter (KHF) and the adaptive hierarchical structure (AHS) incorporating the kinematic properties of the articulated object – are proposed to extend our formulation for the rigid object to the articulated one. Our formulation also allows us to avoid two classic problems in 3D tracking: the multi-view correspondence problem, and the occlusion problem. By adding more cameras and placing them appropriately, our approach can deal with the motion of the object in a very wide area. Furthermore, multiple objects can be handled by managing multiple AHSs and processing multiple HKFs.We show the validity of our approach using the synthetic data acquired simultaneously from the multiple virtual camera in a virtual environment (VE) and real data derived from a moving light display with walking motion. The results confirm that the model-based algorithm works well on the tracking of multiple rigid objects.