CustomCut: On‐demand Extraction of Customized 3D Parts with 2D Sketches

Several applications in shape modeling and exploration require identification and extraction of a 3D shape part matching a 2D sketch. We present CustomCut, an on‐demand part extraction algorithm. Given a sketched query, CustomCut automatically retrieves partially matching shapes from a database, identifies the region optimally matching the query in each shape, and extracts this region to produce a customized part that can be used in various modeling applications. In contrast to earlier work on sketch‐based retrieval of predefined parts, our approach can extract arbitrary parts from input shapes and does not rely on a prior segmentation into semantic components. The method is based on a novel data structure for fast retrieval of partial matches: the randomized compound k‐NN graph built on multi‐view shape projections. We also employ a coarse‐to‐fine strategy to progressively refine part boundaries down to the level of individual faces. Experimental results indicate that our approach provides an intuitive and easy means to extract customized parts from a shape database, and significantly expands the design space for the user. We demonstrate several applications of our method to shape design and exploration.     

Design and application of real-time visual attention model for the exploration of 3D virtual environments

This paper studies the design and application of a novel visual attention model designed to compute user's gaze position automatically, i.e., without using a gaze-tracking system. The model we propose is specifically designed for real-time first-person exploration of 3D virtual environments. It is the first model adapted to this context which can compute in real time a continuous gaze point position instead of a set of 3D objects potentially observed by the user. To do so, contrary to previous models which use a mesh-based representation of visual objects, we introduce a representation based on surface-elements. Our model also simulates visual reflexes and the cognitive processes which take place in the brain such as the gaze behavior associated to first-person navigation in the virtual environment. Our visual attention model combines both bottom-up and top-down components to compute a continuous gaze point position on screen that hopefully matches the user's one. We conducted an experiment to study and compare the performance of our method with a state-of-the-art approach. Our results are found significantly better with sometimes more than 100 percent of accuracy gained. This suggests that computing a gaze point in a 3D virtual environment in real time is possible and is a valid approach, compared to object-based approaches. Finally, we expose different applications of our model when exploring virtual environments. We present different algorithms which can improve or adapt the visual feedback of virtual environments based on gaze information. We first propose a level-of-detail approach that heavily relies on multiple-texture sampling. We show that it is possible to use the gaze information of our visual attention model to increase visual quality where the user is looking, while maintaining a high-refresh rate. Second, we introduce the use of the visual attention model in three visual effects inspired by the human visual system namely: depth-of-field blur, camera- motions, and dynamic luminance. All these effects are computed based on the simulated gaze of the user, and are meant to improve user's sensations in future virtual reality applications.     

A Study on New Virtual Reality System in Maze Terrain

This study proposes the maze virtual reality (MVR) system, which is designed to provide new immersive virtual reality (VR) experiences by generating a maze and an event-based maze environment. The MVR system consists of a maze generation technique based on mazemap, which we additionally propose for the automatic generation of diverse maze patterns, event-enhancing immersion, reducing VR sickness, and interactions. First, we present a finite algorithm that automatically generates diverse maze patterns from the user perspective and implements mazemap for automated three-dimensional (3D) terrain generation from a 2D maze pattern. Then, we present optimized events for the maze environment by providing users with deeper immersion and minimized VR sickness. The design procedure is divided into two elements: an automatic structure for arranging predefined events based on maze pattern analysis and a manual operation module. In addition, a Leap Motion-based interactive scheme is implemented for deeper immersion when the user moves in a limited space, while improving object control. Finally, experiments were conducted to analyze user satisfaction with the MVR system, the psychological impact of the continuous mazemap input, and the effects of the event-based environment on immersion enhancement and VR sickness reduction.     

面向近地表地下空间信息监测的无线传感器网络三维节点部署算法研究

从地下空间的基本特点出发, 提出了地下空间节点部署算法的约束指标, 建立了面向地下空间的自适应、多精度约束的节点部署算法。从网络结构、自适应性、能量消耗及覆盖连通性能等方面对算法进行了分析和仿真, 结果表明该算法能有效地解决近地表地下空间节点的部署问题, 为土壤环境监测、智能交通监测、管道监测及其他地下目标监测提供理论指导和实践依据。     

Tri-view morphing

This paper presents an efficient image-based approach to navigate a scene based on only three wide-baseline uncalibrated images without the explicit use of a 3D model. After automatically recovering corresponding points between each pair of images, an accurate trifocal plane is extracted from the trifocal tensor of these three images. Next, based on a small number of feature marks using a friendly GUI, the correct dense disparity maps are obtained by using our trinocular-stereo algorithm. Employing the barycentric warping scheme with the computed disparity, we can generate an arbitrary novel view within a triangle spanned by three camera centers. Furthermore, after self-calibration of the cameras, 3D objects can be correctly augmented into the virtual environment synthesized by the tri-view morphing algorithm. Three applications of the tri-view morphing algorithm are demonstrated. The first one is 4D video synthesis, which can be used to fill in the gap between a few sparsely located video cameras to synthetically generate a video from a virtual moving camera. This synthetic camera can be used to view the dynamic scene from a novel view instead of the original static camera views. The second application is multiple view morphing, where we can seamlessly fly through the scene over a 2D space constructed by more than three cameras. The last one is dynamic scene synthesis using three still images, where several rigid objects may move in any orientation or direction. After segmenting three reference frames into several layers, the novel views in the dynamic scene can be generated by applying our algorithm. Finally, the experiments are presented to illustrate that a series of photo-realistic virtual views can be generated to fly through a virtual environment covered by several static cameras.     

机器人三维路径规划问题的一种改进蚁群算法

本文研究移动机器人三维空间路径规划问题,针对三维空间的复杂地形特点,提出了一种基于改进蚁群算法的路径规划算法。文中首先描述了一种简单有效的环境建模方法,然后给出了算法在信息素呈现、路径点选取、信息素更新以及启发式函数设计等方面的改进方法。仿真结果证明了算法的可行性和可靠性。     

Fault tolerant embedded systems design by multi-objective optimization

The design of fault tolerant systems is gaining importance in large domains of embedded applications where design constrains are as important as reliability. New software techniques, based on selective application of redundancy, have shown remarkable fault coverage with reduced costs and overheads. However, the large number of different solutions provided by these techniques, and the costly process to assess their reliability, make the design space exploration a very difficult and time-consuming task. This paper proposes the integration of a multi-objective optimization tool with a software hardening environment to perform an automatic design space exploration in the search for the best trade-offs between reliability, cost, and performance. The first tool is commanded by a genetic algorithm which can simultaneously fulfill many design goals thanks to the use of the NSGA-II multi-objective algorithm. The second is a compiler-based infrastructure that automatically produces selective protected (hardened) versions of the software and generates accurate overhead reports and fault coverage estimations. The advantages of our proposal are illustrated by means of a complex and detailed case study involving a typical embedded application, the AES (Advanced Encryption Standard).     

基于双目立体视觉的机械手精确定位系统

在机械手执行任务的过程中,控制机械手定位到目标位置是一个非常的机械手自动定位系统设计方法,由双目立体视觉系统根据目标物的二维图像计算出目标物的三维坐标,然后根据此三维坐标去控制机械手自动运动到目标位置.实验表明该系统能提高排爆机器人机械手的易操作性,大大提高了机械手的性能     

3D Target Scale Estimation and Target Feature Separation for Size Preserving Tracking in PTZ Video

To achieve size preserving tracking, in addition to controlling the camera’s pan and tilt motions to keep the object of interest in the camera’s field of view (FOV), the camera’s focal length is adjusted automatically to compensate for the changes in the target’s image size caused by the relative motion between the camera and the target. The estimation accuracy of these changes determines the effectiveness of the resulting zoom control. The existing method of choice for real-time target scale estimation applies structure from motion (SFM) based on the weak perspective projection model. In this paper we propose a target scale estimation algorithm with a linear solution based on the more advanced paraperspective projection model, which improves the accuracy of scale estimation by considering center offset. Another key issue in SFM based algorithms is the separation of target and background features, especially when composite camera (pan/tilt/zoom) and target motions are involved. This paper designs a fast target feature separation/grouping algorithm, the 3D affine shape method. The resulting separation automatically adapts to the target’s 3D geometry and motion and is able to accommodate a large amount of off-plane rotation, which most existing separation/grouping algorithms find difficult to achieve. Experimental results illustrate the effectiveness of the proposed scale estimation and feature separation algorithms in tracking translating and rotating objects with a PTZ camera while preserving their sizes. In comparison with the leading size preserving tracking algorithm described by Tordoff and Murray, our algorithm is able to reduce the cumulative tracking error significantly from 17.4% to 3.3%.     

一种牙种植三维数字化定位导板的生成算法

采用数字图像技术和科学可视化技术,提出一种对外科牙种植的植入位置、深度及方向上具有定位导航作用的手术导板生成算法。针对具有个体差异的颌骨三维结构进行重采样,以拟合样条曲线完成对种植区域勾画,并分割提取目标区域数据进行三维重建,以生成虚拟数字化导板算法,结合可视化工具包VTK在Visual Studio 2005平台下编程,实现了根据颌骨三维结构特征自动生成虚拟导向模板的功能。实验结果表明,与传统的方法相比,牙种植导向模板的制作更加简便、快捷、有效。     

自适应T样条曲面重建

为了进行快速高精度的曲面重建,提出了一种新的基于T样条的曲面自动重建算法。由于T样条控制网格具有特殊性质,因此在使用T样条进行曲面重建时,一个关键的问题是如何构造好一个T网格。该新算法在进行曲面重建时,用三角网格的参数化方法,先将数据点同胚映射到平面,然后再利用平面四叉树细分的方法将无结构散乱数据自动生成合理有效的T网格,最后将曲面重构模型转化为最优化问题,并由最小二乘法求解,同时在误差较大的区域辅以T样条的局部修正,以使重建曲面与原网格面的最大误差小于指定的误差值。由于该新的曲面重建方法是一个基于细节的重建方法,因此采样点密集区域所插入的T网格点也就相应地增多,这样既抓住了网格曲面的特征,又能很好地减少过多的T网格控制顶点,这就提高了算法效率。另外,该新算法还具有高效、易操作、能适应复杂曲面重建、曲面自动生成且满足相应精度要求等优点。重构结果显示,该新的曲面重建算法不仅重构应用范围广,且重构精度高。     

符号方案三维实体化的自动化方法研究

如何将创新设计过程中得到的符号方案生成直观的图形方案，是机械概念设计中的关键技术问题，通过对符号方案的邻接矩阵元素进行分析，得到机构的结构组成、构件连接关系等信息；运用符号方案的尺度矩阵确定各装配构件的二维几何尺度，在面向对象二次开发的环境下，基于三维参数化平台，实现构件的三维实体化；根据构件所处空间位置，按后台预置装配方法得到三维虚拟实体装配图。上述过程基于面向对象的环境，输入／读入概念设计得到符号方案后，系统自动地将符号方案生成三维虚拟实体方案。     

伪三维的地理位置无线传感器网络路由算法

针对实际应用中传感器网络大多分布在山地丘陵等起伏地势环境下,在研究基于地理位置路由算法的基础上,结合无线传感器网络分布的地势环境,提出了伪三维的地理位置无线传感器网络路由算法。该算法利用电子地图,计算节点间沿起伏地势的近似最短路径,路由过程中根据地理位置信息选择下一跳时,用当前节点和邻居节点到目标节点在起伏地势上的最短路径代替空间欧氏距离。实验仿真证明,与目前使用较多的三维贪婪路由算法相比,该算法能有效减少数据在转发过程中的路由跳数。     

一种基于多重共线性的三维DV-Hop定位算法

针对多边测距法的不足,考虑定位算法所应用的现实环境,在典型DV-Hop算法的基础上,提出了一种改进的三维定位算法。该算法除了将DV-Hop定位算法从二维空间移植到三维空间以外,着重考虑了信标节点拓扑关系和跳数对定位精度的影响,提出一种基于多重共线性的三维DV-Hop定位算法MCB3D DV-Hop。该算法通过设置跳数阂值与多重共线性阂值两个阂值参数,挑选网络中好的信标节点组进行位置估计。理论分析和仿真实验结果表明了算法有较高的定位精度和稳定性。     

3维灰度矩阵的钢板缺陷图像识别

目的 钢板表面缺陷的种类多样、灰度结构复杂,现有的图像分割技术运用在灰度结构复杂、目标边缘模糊的钢板缺陷图像中仍然存在识别效率低、过分割现象明显等问题,本文结合图像灰度矩阵的空间特征,提出一种基于3维灰度矩阵的钢板表面缺陷识别算法。方法 首先根据灰度图像构建3维灰度矩阵;然后引入半类间方差改进克里金插值算法,绘制3维灰度矩阵的等值线图;接着构建等值线的拓扑关系树;最后根据自定义的全局搜索策略和局部搜索策略相结合,寻找局部凹凸区域,从而定位缺陷区域,达到分割钢板表面缺陷的目的。结果 本文方法能有效地识别钢板表面缺陷区域,对光照变化不敏感,在保证低误差率的前提下,提高了有效分割率。通过对氧化、辊印、结疤和气泡四类钢板缺陷图像进行测试,从分割效果和评价指标两方面对比其他钢板缺陷分割算法。与Fisher阈值分割法、经典的活动轮廓模型CV模型、基于半局部区域描述符的活动轮廓模型HTB模型和改进背景差分法进行分割效果对比,本文方法对四类钢板表面缺陷的识别更精确,分割结果更细致,一定程度上抑制了过分割现象。与大津法Ostu、1维最大模糊熵法1DMFE、最大模糊超熵法MFEE进行评价指标对比,得出对于分割孔洞和辊印图像,本文方法在误分割率均保持在2.0%以下的前提下,将有效信息率分别提升了1.6%和2.1%;对于夹杂图像,本文方法在3.4%的误分割率的前提下,具有85%以上的有效信息率。结论 提出的基于3维灰度矩阵的钢板缺陷图像识别算法可以有效地识别多种类型的钢板缺陷,即使在缺陷结构复杂的图像识别中仍具有较高的识别率。     

多传感器基于动态时空特性软硬协作决策的目标检测研究

针对多传感器系统中目标检测时检测精度与效率的矛盾问题,研究了一种具有协同合作决策功能的目标检测算法及其传感器设计方案。首先将多传感器系统依据时域、空域和频域给出三维定义描述,分析了时空动态特性,其次依据二元检验和目标优化检测分析了软决策和硬决策在目标检测时变化规律,建立了一种基于协同合作的目标检测决策机制,最后给出了基于动态时空特性软硬协作决策的目标检测及其传感器头结构设计方案。实验表明,所提目标检测方案在检测精度、检测效率、资源利用率和覆盖率等方面具有明显优势。     

改进YOLO V2的6D目标姿态估计算法

针对目标的三维姿态估计,结合基于深度学习的目标检测模型,提出一种基于改进YOLO V2的6D目标姿态估计算法。通过卷积神经网络提取一幅RGB图像中目标的特征信息;在2D检测的基础上将目标的位置信息映射到三维空间;利用点到点的映射关系在三维空间匹配并计算目标的自由度,进而估计目标的6D姿态。该算法不仅能检测单幅RGB图像中的目标,还可以预测目标的6D姿态,同时不需要额外的后处理过程。实验表明,该算法在LineMod和Occlusion LineMod数据集上的性能优于最近提出的其他基于CNN的方法,在Titan X GPU上的运行速度是37?frame/s,适合实时处理。     

基于空间投影的管道施工图自动生成研究

为满足企业对锅炉管道施工图的快速生成需求,基于给定的管道信息,结 合投影规律,提出并实现了基于三维空间定位点的管道自动施工图生成算法,该算法能够自 动确定主视图的方向,自动对图形进行打断,自动完成二面角视图以及局部视图的判断和绘 制。通过在企业的实际应用中证明了算法的可靠和高效。