Surface and normal ensembles for surface reconstruction

The majority of the existing techniques for surface reconstruction and the closely related problem of normal reconstruction are deterministic. Their main advantages are the speed and, given a reasonably good initial input, the high quality of the reconstructed surfaces. Nevertheless, their deterministic nature may hinder them from effectively handling incomplete data with noise and outliers. An ensemble is a statistical technique which can improve the performance of deterministic algorithms by putting them into a statistics based probabilistic setting. In this paper, we study the suitability of ensembles in normal and surface reconstruction. We experimented with a widely used normal reconstruction technique [Hoppe H, DeRose T, Duchamp T, McDonald J, Stuetzle W. Surface reconstruction from unorganized points. Computer Graphics 1992;71-8] and Multi-level Partitions of Unity implicits for surface reconstruction [Ohtake Y, Belyaev A, Alexa M, Turk G, Seidel H-P. Multi-level partition of unity implicits. ACM Transactions on Graphics 2003;22(3):463-70], showing that normal and surface ensembles can successfully be combined to handle noisy point sets.     

Constraint-based beautification and dimensioning of 3D polyhedral models reconstructed from 2D sketches

3D models reconstructed from 2D sketches are inaccurate because of the inherent inaccuracies in the input and the reconstruction method. It is therefore necessary to “beautify” them before use in CAD systems. We present a method that detects geometric constraints, such as parallel and orthogonal faces, present in the reconstructed model and then selects a subset that constrains the object sufficiently and consistently. The subset selection algorithm first prioritizes the constraints depending on their type and then uses a novel method, based on quasi-Newton optimization, to detect and eliminate redundant and inconsistent constraints. The remaining constraints then define the dimensions of the model fully and consistently. Results from our implementation show that the method can beautify and dimension recovered 3D models correctly at acceptable speed.     

Optimal control of nonlinear systems to given orbits

Using optimal control techniques we derive and demonstrate the use of an explicit single-step control method for directing a nonlinear system to a target orbit and keeping it there. We require that control values remain near the uncontrolled settings. The full nonlinearity of the problem in state space variables is retained. The “one-step” of the control is typically a composition of known or learned maps over (a) the time required to learn the state, (b) the time to compute the control and (c) the time to apply the control. No special targeting is required, yet the time to control is quite rapid. Working with the dynamics of a well-studied nonlinear electrical circuit, we show how this method works efficiently and accurately in two situations: when the known circuit equations are used, and when control is performed only on a Poincaré section of the reconstructed phase space. In each case, because the control rule is known analytically, the control strategy is computationally efficient while retaining high accuracy. The target locations on the selected target trajectory at each control stage are determined dynamically by the initial conditions and the system dynamics, and the target trajectory is an approximation to an unstable periodic orbit of the uncontrolled system. A linear stability analysis shows that dissipation in the dynamical system is essential for reaching a controllable state.     

Quantitative studies on the movement of fluid and lymphocytes through periodontal tissue and into the draining lymph.

Chronic lymph drainage techniques in sheep have been used to map the pathways and to quantify the fluid and cell traffic through periodontal tissues. The continuous collection of cervical and prescapular lymph has demonstrated that 65% of labelled protein tracer injected into the periodontal tissues could be found in lymph over a period of 7.5 hours. Nearly 90% of the total radioactivity could be accounted for between the lymph and the tissue site. When silk was impregnated with radiolabelled albumin and a tooth ligated, the kinetics of the subsequent appearance of the tracer in lymph emphasized the ease with which macromolecules surrounding the teeth gain access to the lymphatics, regional lymph nodes, and immune apparatus. Animals were primed with BCG and then tuberculin (delayed hypersensitivity) lesions were simultaneously induced in the skin, bowel, and periodontium. When T cells were labelled with radioisotopes and their migration from blood to lymph measured, the periodontal tissue traffic pattern was distinct from the traffic pattern through DTH in the skin and also distinct from the pattern through the small intestine. This indicates that the lymphocyte traffic through the inflamed periodontium has unique features. This tissue specificity was not apparent when lesions were induced with TNFalpha. The static assessment of lymphocyte subsets within the tissues was also assessed with immunohistochemistry.     

虚拟肝脏的规则和非规则手术切除技术

为了提高肝癌手术治疗计划的可靠性,在利用腹部CT图像数据进行肝脏三维重建的基础上,实现了任意角度对虚拟肝脏进行平面切割和切割面结构的显示;通过构造可以调节大小、位置的球体模型,实现了球体切除;通过在肝脏三维模型表面上勾画不规则封闭区域,实现了任意曲面肝脏切除;并依据肝内血管结构进行肝段划分,实现了解剖性肝段切除.临床实验结果表明,文中所述的技术能够满足虚拟手术的需求,有利于医生制定安全可靠的术前计划,提高手术成功率.     

MC算法在医学图像三维重建中的应用

详细介绍了MC算法,提出了优化网格模型简化算法。优化网格模型简化算法选取坐标点的原则是,尽可能地接近原始网格,通常采用子集选择法或优化选择法。在尽可能保证图像精度的前提下,优化网格模型简化算法可以提高运算速度,而单纯的网格算法由于失真严重而缺乏实用价值。基于体绘制的网格化简化算法重建的三维模型比较完全,且算法简单,在多排螺旋CT等医学图像三维重建中有较好的应用。     

一种低复杂度的鲁棒自适应波束形成算法

传统基于干扰噪声协方差矩阵（interference-plus-noise covariance matrix,INCM）重构的鲁棒自适应波束形成（robust adaptive beamformer,RAB）算法在多种样本数据协方差矩阵误差和信号导向向量误差的失配环境中具有较强的鲁棒性,但目前主流的INCM重构法都是对信号和干扰的导向向量通过建立凸优化模型来估计,这带来了很高的计算复杂度。为了解决这个问题,提出了一种低复杂度的基于INCM重构的RAB算法。该算法首先将干扰信号的导向向量分解为对应标称项和误差项的和,然后通过一种子空间方法估计得到误差项的单位向量。接下来对一个Capon空间谱功率最大问题进行求解,得到误差项的模值,以此得到重构的INCM。同时利用Capon空间谱中残差噪声的存在,使用交替投影法估计得到期望信号的导向向量,最后得到所提算法的权重向量。仿真实验表明所提算法在多种误差环境下具有较强鲁棒性的同时,还具有较低的计算复杂度。     

A robot hand-eye calibration method of line laser sensor based on 3D reconstruction

In the robotic eye-in-hand measurement system, a hand-eye calibration method is essential. From the perspective of 3D reconstruction, this paper first analyzes the influence of the line laser sensor hand-eye calibration error on the 3D reconstructed point clouds error. Based on this, considering the influence of line laser sensor measurement errors and the need for high efficiency and convenience in robotic manufacturing systems, this paper proposes a 3D reconstruction-based robot line laser hand-eye calibration method. In this method, combined with the point cloud registration technique, the newly defined error-index more intuitively reflects the calibration result than traditional methods. To raise the performance of the calibration algorithm, a Particle Swarm Optimization - Gaussian Process (PSO-GP) method is adopted to improve the efficiency of the calibration. The experiments show that the Root Mean Square Error (RMSE) of the reconstructed point cloud can reach 0.1256 mm when using the proposed method, and the reprojection error is superior to those using traditional hand-eye calibration methods.     

嵌入式虚拟仪器软件可重构设计技术研究

嵌入式虚拟仪器(EVI)软件可重构是指框架和功能的重构;结合面向对象技术和组件技术,系统地阐述了软件可重构模块化设计的原理、软件可重构算法、可重构软件结构框架设计和可重构软件开发方法;通过分析可重构软件的设计原理和设计思路,提出了一套比较详细的可重构软件的开发方法;经工程实践应用,设计方法合理可行,有效提高了嵌入式虚拟仪器软件的开发效率,达到软件复用及重构的目的。     

考虑客户画像和能量枢纽的配电网多目标抢修重构模型

随着大规模风电以及能量枢纽接入配电网,配电网故障后抢修重构面临新挑战,提出一种考虑客户画像和能量枢纽的配电网多目标多故障抢修重构模型。通过对配电网用电客户多因素精准画像,确定权重,建立兼顾客户画像和能量枢纽的配电网多目标抢修重构模型,提出一种改进NSGA-II算法以适应对模型求解,从而获得Pareto解集,并利用模糊最大满意度进行决策。算例仿真表明所提模型正确有效,与传统模型相比更加精细而客观。