复杂三维曲面覆盖算法研究

针对无线传感器网络中三维空间曲面覆盖问题进行研究,建立传感器节点的三维感知模型,考虑到曲面的不规则性,曲面凸点会成为节点感知过程中的障碍物,形成三维空间中特有的三维感知盲区。首先从理论上对简单曲面进行分析,计算出实现有限曲面全覆盖所需的最少节点数,在对三维曲面进行网格划分以及根据三维感知盲区改进适应度函数后,引入差分进化（DE）算法对随机部署在三维空间中的传感器节点的位置坐标进行优化,通过大量仿真实验得出实现目标曲面全覆盖所需的最少的节点数,引入误差率,通过提出的测试准则验证了引用DE算法解决简单三维曲面覆盖问题的有效性。最后将DE算法运用到解决复杂三维曲面覆盖问题中,取得了良好的效果。     

SO dynamic deformation for building of 3-D models

Three-dimensional (3D) modeling based on an ensemble of multilayer self-organizing (SO) neural networks is described. Our objective for 3D modeling is to construct a representation of a 3D object shape from sensed surface points acquired from the object. Current modeling techniques can be classified into two categories: the static and the dynamic approaches, where the former grounded in computational geometry, and the latter rooted in the mechanics of elastic materials. In this paper, a neural-based dynamic modeling approach is presented. The method used is proved to converge and experimental results are shown which support its applicability to real problems.     

3TP: an application-Layer protocol for streaming 3-D models

This paper addresses the problem of streaming progressively compressed three-dimensional (3-D) models over lossy networks. Out of all encoded packets that can be transmitted, we intelligently choose a subset of packets to be transmitted using transport control protocol in order to meet a distortion constraint, while transmitting the remaining packets using user datagram protocol to minimize the end-to-end delay. We call this new application-layer protocol 3-D models transport protocol. We show the effectiveness of this protocol both experimentally and theoretically. We compare the performance of the proposed protocol with systems that do not optimize transmission according to the content of the encoded bitstream. When the maximum distortion is 30, measured using the Hausdorff distance, we achieve savings in delay time ranging from 39% to 68% for packet-loss rates between 1% and 19%.     

Finite-element methods for active contour models and balloons for2-D and 3-D images

The use of energy-minimizing curves, known as “snakes” to extract features of interest in images has been introduced by Kass, Witkin and Terzopoulos (1987). A balloon model was introduced by Cohen (1991) as a way to generalize and solve some of the problems encountered with the original method. A 3-D generalization of the balloon model as a 3-D deformable surface, which evolves in 3-D images, is presented. It is deformed under the action of internal and external forces attracting the surface toward detected edgels by means of an attraction potential. We also show properties of energy-minimizing surfaces concerning their relationship with 3-D edge points. To solve the minimization problem for a surface, two simplified approaches are shown first, defining a 3-D surface as a series of 2-D planar curves. Then, after comparing finite-element method and finite-difference method in the 2-D problem, we solve the 3-D model using the finite-element method yielding greater stability and faster convergence. This model is applied for segmenting magnetic resonance images     

非规则三维数据的曲面拟合方法

给出了一种非规则三维数据的曲面拟合方法,该方法给出的网络模型不需要删除奇异数据,从而可以保持数据信息的完整性,此外,该方法给出的拟合曲面平滑,连续性好,局部细节丰富,且处处可偏导。     

Neural-network-based adaptive hybrid-reflectance model for 3-D surface reconstruction

This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D) surface reconstruction model. The neural network automatically combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pixel values of the two-dimensional images to be reconstructed. The normal vectors of the surface can then be obtained from the output of the neural network after supervised learning, where the illuminant direction does not have to be known in advance. Finally, the obtained normal vectors are applied to enforce integrability when reconstructing 3-D objects. Facial images and images of other general objects were used to test the proposed approach. The experimental results demonstrate that the proposed neural-network-based adaptive hybrid-reflectance model can be successfully applied to objects generally, and perform 3-D surface reconstruction better than some existing approaches.     

Constructing 3-D object models using multiple simulated 2.5-D sketches

Many applications involve the construction of 3-D object models from which images, often requiring a high degree of realism, are later produced. Constructing such models frequently involves considerable human intervention, even in cases where a physical model or the actual object to be modelled exists. This paper describes an approach to the automatic construction of 3-D object models using images of scenes. This method employs a representation of the visible surfaces in a scene called the 2.5-D sketch and a model construction process is described that utilizes multiple simulated 2.5-D sketches.     

A neurofuzzy-based quality-control system for fine pitch stencil printing process in surface mount assembly

Surface mount assembly defect problems can cause significant production-time losses. About 60% of surface mount assembly defects can be attributed to the solder paste stencil printing process. This paper proposes a neurofuzzy-based quality-control system for the fine pitch stencil printing process. The neurofuzzy approach is used to model the nonlinear behavior of the stencil printing process. Eight control variables are defined for process planning and control, including stencil thickness, component pitch, aperture area, snap-off height, squeegee speed, squeegee pressure, solder paste viscosity, and solder paste particle size. The response variables are the volume and height of solder paste deposited. The values of the response variables provide indicators for identifying potential quality problems. A 3^8–3 fractional factorial experimental design is conducted to collect structured data to augment those collected from the production line for neurofuzzy learning and modeling. Visual basic programming language is then used for both rule retrieval and graphical-user-interface modeling. The effectiveness of the proposed system is illustrated through a real-world application.     

3-D surface description from binocular stereo

A stereo vision system that attempts to achieve robustness with respect to scene characteristics, from textured outdoor scenes to environments composed of highly regular man-made objects is presented. It integrates area-based and feature-based primitives. The area-based processing provides a dense disparity map, and the feature-based processing provides an accurate location of discontinuities. An area-based cross correlation, an ordering constraint, and a weak surface smoothness assumption are used to produce an initial disparity map. This disparity map is only a blurred version of the true one because of the smoothing introduced by the cross correlation. The problem can be reduced by introducing edge information. The disparity map is smoothed and the unsupported points removed. This method gives an active role to edgels parallel to the epipolar lines, whereas they are discarded in most feature-based systems. Very good results have been obtained on complex scenes in different domains     

Application of 3-D models to computer vision

A flexible computer vision is described which is able to recognize 3-D objects if their models are given. The models can be built in a CAD process using a geometric modeler GEOMAP. Three cases are studied: surface normals are available, a part of surface normals are available, and range data is available. In order to perform efficient matching, three methods are proposed for those cases: use of EGI representation, use of relative angles between surface normals, and use of kernels.     

Acquiring 3-D models from sequences of contours

This paper explores shape from contour for acquiring 3-D graphics models. In this method, a continuous sequence of images is taken as an object rotates. A smooth convex shape can be estimated instantaneously from its contour and by the first derivative of contour movement (trace of contour, or contour distribution with time). We also analyze shapes that do not satisfy the conditions of smoothness and visibility, which are indispensable for modeling an object. A region that does not expose as contour yields a nonsmoothness in the tracked contour movement. We can thus detect such a region by contour distribution filtering and extract its accurate location by computing the left and right derivatives of the distribution. This has not been studied previously. These unknown regions are obtained for further investigation using other visual cues. A general approach for building a geometrical object model using contours is then described. The entire process from silhouettes to a 3-D model is based local computation; this is promising for producing shapes in real time. Our direct goal is to establish 3-D graphics models of human faces for the growing needs of visual communications. We have obtained some good results     

Retrieving articulated 3-D models using medial surfaces

We consider the use of medial surfaces to represent symmetries of 3-D objects. This allows for a qualitative abstraction based on a directed acyclic graph of components and also a degree of invariance to a variety of transformations including the articulation of parts. We demonstrate the use of this representation for 3-D object model retrieval. Our formulation uses the geometric information associated with each node along with an eigenvalue labeling of the adjacency matrix of the subgraph rooted at that node. We present comparative retrieval results against the techniques of shape distributions (Osada et al.) and harmonic spheres (Kazhdan et al.) on 425 models from the McGill Shape Benchmark, representing 19 object classes. For objects with articulating parts, the precision vs recall curves using our method are consistently above and to the right of those of the other two techniques, demonstrating superior retrieval performance. For objects that are rigid, our method gives results that compare favorably with these methods. A preliminary version of this article was published in EMMCVPR 2005. In this extended version we have included results on the significantly larger McGill Shape Benchmark, making a stronger case for the advantages of our method for models with articulating parts. We have also included expanded introduction, medial surface computation, matching, indexing, experimental results, and discussion sections, along with several new figures.     

Geological uncertainties associated with 3-D subsurface models

Subsurface models are generally built from both subjective interpretation and mathematical interpolation/extrapolation techniques. These models are therefore uncertain, but their uncertainty is rarely expressed in a geological forecast. In this paper, an evaluation method of geological uncertainties related to 3-D subsurface models is proposed and tested on a real case. This method is based on the subsurface model, which is considered the most probable prediction (best guess). The various geological interfaces are handled as Gaussian random fields to which a model of spatial variability describing possible fluctuations around the best guess is applied. Several structural constraints, such as the shape of folds and thickness of layers are accounted for in the model. At this point, the local variance can be estimated throughout the study area by application of the simple kriging technique. Finally, the variability is converted into probabilities of occurrence of the various rock masses present in the study area. The probabilities are calculated according to intersection rules governing the stratigraphic sequence of the subsurface model. They enable one to probabilistically model subsurface structures in the form of a three-dimensional (3-D) probability field.     

Hybrid simulation models for spare parts supply chain considering 3D printing capabilities

In the era of Industry 4.0, 3D printing unlocks a wide array of solutions to rapidly-produce spare parts for maintenance operations. In this research, we propose a hybrid simulation approach, combining agent-based and discrete event simulation methods, to investigate how the adoption of 3D printing technologies to manufacture spare parts for maintenance operations will improve operational efficiency and effectiveness. Specifically, our framework is applied to the United States Navy’s fighter jet maintenance operations to study various network configurations, where 3D printing facilities may be centralized, decentralized, or hub configured. System performance in terms of the total cost, timeliness of delivery, and vulnerability under disruptions such as cyber-attacks and emergencies are evaluated. Lastly, the impact of 3D printing technological advancements on operational performance is investigated to obtain managerial insights.     

An interactive framework for acquiring vision models of 3-D objects from 2-D images.

This paper presents a human-computer interaction (HCI) framework for building vision models of three-dimensional (3-D) objects from their two-dimensional (2-D) images. Our framework is based on two guiding principles of HCI: 1) provide the human with as much visual assistance as possible to help the human make a correct input; and 2) verify each input provided by the human for its consistency with the inputs previously provided. For example, when stereo correspondence information is elicited from a human, his/her job is facilitated by superimposing epipolar lines on the images. Although that reduces the possibility of error in the human marked correspondences, such errors are not entirely eliminated because there can be multiple candidate points close together for complex objects. For another example, when pose-to-pose correspondence is sought from a human, his/her job is made easier by allowing the human to rotate the partial model constructed in the previous pose in relation to the partial model for the current pose. While this facility reduces the incidence of human-supplied pose-to-pose correspondence errors, such errors cannot be eliminated entirely because of confusion created when multiple candidate features exist close together. Each input provided by the human is therefore checked against the previous inputs by invoking situation-specific constraints. Different types of constraints (and different human-computer interaction protocols) are needed for the extraction of polygonal features and for the extraction of curved features. We will show results on both polygonal objects and object containing curved features.     

基于三维拼接技术的三维测量系统的开发

提出一种利用参考底座对三维数据进行剪裁拼接的新方法并应用于360°三维全场测量.通过对测量算法、控制软件、云台以及计算机串口通信的系列研究,开发出相应的程序和控制硬件,最终建立了采用面结构光照明的、自动化的360°三维形貌测量系统.该系统给工业三维全场测量提供了一个可操作平台,精确度也达到了实用要求.     

A 3-D vision system model for automatic object surface sensing

The development of a noncontact light striping (structured light) based three-dimensional, six-degrees-of-freedom vision system for automatic object surface sensing is reported. The system modeling and world-point reconstruction methodology involve homogeneous-coordinate system transformations applied in two independent stages: the video imaging stage using three-dimensional perspective transformations and the mechanical scanning stage using three-dimensional affine transformations. Concatenation of the two independent matrix models leads to a robust four-by-four, six-degrees-of-freedom system model. The reconstructed sectional contours are registered automatically in real time with respect to a common world-coordinate system as a control net for Non-Uniform Rational B-spline (NURBS) surface approximation. The reconstruction process is demonstrated by measuring the surface of a 19.5×2 ft rowing shell. A detailed statistical accuracy and precision analysis shows an average error of 0.2% (0.002) of the camera's field-of-view. System sensitivity analysis reveals a nonlinear increase of sensitivity for angles higher than 45° between the normals of the image and laser planes.     

基于打印聚合物薄膜技术的NH_3传感器

研究了一种新型的采用打印技术的NH3传感器,探讨了打印"墨水"材料聚苯胺和聚吡咯的制备和"墨水"掺酸比例对NH3传感器敏感度的影响。为了提高传感器灵敏度,分别对传感器的直流和交流阻抗特性进行了研究。结果发现在1.5 kHz左右交流阻抗的测试条件下,传感器灵敏度要较直流阻抗测试高近1个数量级。此外还通过构建1个交流阻抗拟合模型对传感器交流阻抗变化过程作了解释。研究的采用打印技术基于聚合物的NH3传感器具有成本低,可以制作在柔性衬底上和适合大规模生产等特点,在食品加工、养殖业和医疗等领域具有广泛的应用前景。