一种人工标志点自动匹配的方法

给出了一种自动识别和匹配人工标志点的方法。该方法包括设计一套具有唯一特征的人工标志点和对该套标志点进行自动识别和匹配两部分内容。详细讨论了自动识别和匹配标志点算法中的各个步骤,包括标志点的判定、标志点的标定和标志点的匹配。该方法将有效地解决计算机辅助近景摄影测量中人工标志点的自动匹配难题。     

一种圆形编码标志点的设计及解码算法研究

为提高大尺寸摄影测量中编码标志点编码容量和解码准确率,设计一种由定位圆、起始圆和编码圆组成编码标志点.解码时,按圆度和面积提取、区分各种圆;对编码标志点进行透视变换实现编码圆的位置校正;对校正后的编码标志点解码.分别在物、象平面夹角为0°,45°,60°和室外复杂场景进行了实验,解码准确率均可达到100％.实验结果表明:编码标志点具有方便提取和识别、编码容量大、鲁棒性强等优点,为大尺寸摄影测量中数据拼接提供一种新的编码标志点.     

多介质下空间目标的视觉测量

基于计算机视觉的无接触三维测量原理和光的折射定律,提出一种多介质下空间目标视觉测量方法。采用多相机捆绑调整及多角度相互校正,通过双目立体视觉技术结合光线在多介质中发生两次折射的数学模型对运动体上各标志点进行测量,获取各标志点的三维空间坐标,经平面拟合、坐标转换,最终解算得到运动体六自由度空间坐标。实验结果表明,该方法适用于多介质视觉测量,具有较高的测量精度和良好的稳定性。     

基于3S及互联网的测量标志点巡查管理系统

基于互联网的3s技术综合了GIS,GPS,RS及3G互联网通讯等的多种技术手段,并且在各行业应用中逐步走向成熟本文着重阐述了测量标志点巡查网系统的主要功能、实现方法。通过该系统,实现了测量标志点外业巡查及内外管理的实时联动,提高了保护测量标志点的工作效率。     

姿态和表情变化下的三维人脸标志点定位

三维人脸标志点定位在人脸识别、人脸跟踪、人脸建模、表情分析等方面具有非常重要的作用. 然而, 在姿态和表情变化很大的条件下进行标志点定位, 这仍然是一个很具挑战性的课题. 本文提出一种对姿态和表情不敏感的三维人脸标志点定位方法, 利用HK曲率分析检测出候选标志点, 根据对面部形状的先验知识, 提出一种基于人脸几何结构的分类策略对候选标志点进一步细分, 通过把候选标志点与人脸标志点模型进行匹配, 实现标志点的精确定位. 首先在CASIA数据集对该方法的标志点定位精度进行测试, 然后在UND/FRGC v2.0数据集对该方法与其他方法进行比较. 实验结果表明该方法在姿态和表情变化很大的条件下具有高精度和高鲁棒性.     

姿态和表情变化下的三维人脸标志点定位（英文）

三维人脸标志点定位在人脸识别、人脸跟踪、人脸建模、表情分析等方面具有非常重要的作用.然而,在姿态和表情变化很大的条件下进行标志点定位,这仍然是一个很具挑战性的课题.本文提出一种对姿态和表情不敏感的三维人脸标志点定位方法,利用HK曲率分析检测出候选标志点,根据对面部形状的先验知识,提出一种基于人脸几何结构的分类策略对候选标志点进一步细分,通过把候选标志点与人脸标志点模型进行匹配,实现标志点的精确定位.首先在CASIA数据集对该方法的标志点定位精度进行测试,然后在UND/FRGC v2.0数据集对该方法与其他方法进行比较.实验结果表明该方法在姿态和表情变化很大的条件下具有高精度和高鲁棒性.     

自由曲面视觉测量标志点三维匹配方法研究

提出一种适用于自由曲面视觉测量的标志点三维匹配方法.该方法首先通过编码标志点确定局部测量区域在物体上的初始位置,获得可能匹配点集;然后根据非编码标志点与编码标志点之间的距离、角度、方向等特征,获得全局坐标系与局部坐标系之间的初始转换关系;最后根据此初始转换关系求解最终匹配点集,完成标志点的三维匹配.该方法适用于基于标志...     

多尺度信息融合的船舶外板检测三维标志点识别方法

针对船舶外板开展数字化检测技术研究对提升船舶外板智能制造水平具有重要意义。为解决船舶外板检测参考点坐标获取问题,提出了一种识别三维标志点的方法,可在船舶外板数字化检测过程中为实测点云和模型点云的匹配提供参考坐标信息。该方法针对船舶外板结构特点和形面测量需求,设计三维标志点的几何结构。此外,结合三维标志点自身多种特征和周边结构差异化特征,将标志点多种尺度信息进行融合,实现对标志点的精准识别。最后通过标志点测量数据计算对应船舶外板上定位点的三维坐标。通过试验验证了在所提出的方法在三维标志点识别方面具有准确性高、定位精准的优点,将大幅提升船舶外板数字化检测的效率。     

八叉树搜索算法在计算机辅助手术中的应用

讨论基于八叉树的空间搜索与求交算法,包括基于八叉树的单元格分配及求交运算2个步骤。该算法可有效应用于计算机辅助手术,实现解剖标志点的空间定位、距离测量、骨厚测量、三维模型间的干涉与距离检测等。其运算效率较高,具有良好的通用性和扩展性,适用于各类计算机辅助手术规划与手术导航软件。     

近景摄影测量中人工标志点的提取方法研究

针对近景摄影测量中人工标志点的自动识别问题,提出了一种人工标志点的中心坐标提取方法。在布设了多个标志点的隧道断面图像中,通过背景消除、形态学处理、标志点区域划分和非标志点消除等过程,能够识别出人工标志点并提取其中心坐标,并运用近景摄影测量的相关技术计算出其实际坐标。上述方法通过VC++编程得到了实现,其结果说明了该方法的可行性。     

Using parallel line information for vision-based landmark location estimation and an application to automatic helicopter landing

An approach to landmark location estimation by computer vision techniques is proposed. The objective is to derive the position and the orientation of the landmark with respect to the vehicle by a single image. Such information is necessary for automatic vehicle navigation. This approach requires lower hardware cost and simple computation. The vanishing points of the parallel lines on the landmark are used to detect the landmark orientation. The detected vanishing points are used to derive the relative orientation between the landmark and the camera, which is then utilized to compute the landmark orientation with respect to the vehicle. The size of the landmark is used to determine the landmark position. Sets of collinear points are extracted from the landmark and their inter-point distances are computed. The positions of the collinear point sets are evaluated and used to determine the landmark position. Landing site location estimation by using the identification marking H on the helicopter landing site for automatic helicopter landing is presented as an application of the proposed approach. Simulations and experiments have been conducted to prove the feasibility of the proposed approach.     

Using parallel line information for vision-based landmark location estimation and an application to automatic helicopter landing

An approach to landmark location estimation by computer vision techniques is proposed. The objective is to derive the position and the orientation of the landmark with respect to the vehicle by a single image. Such information is necessary for automatic vehicle navigation. This approach requires lower hardware cost and simple computation. The vanishing points of the parallel lines on the landmark are used to detect the landmark orientation. The detected vanishing points are used to derive the relative orientation between the landmark and the camera, which is then utilized to compute the landmark orientation with respect to the vehicle. The size of the landmark is used to determine the landmark position. Sets of collinear points are extracted from the landmark and their inter-point distances are computed. The positions of the collinear point sets are evaluated and used to determine the landmark position. Landing site location estimation by using the identification marking H on the helicopter landing site for automatic helicopter landing is presented as an application of the proposed approach. Simulations and experiments have been conducted to prove the feasibility of the proposed approach.     

求连续搅拌釜式反应器控制系统数学模型的计算机程序

信号流图是一种表示复杂控制系统中各变量间关系的很好的方法。利用 MASON 增益公式可以求得信号流图中输入变量与输出变量间的关系—即输入节点到输出节点的总传输。本文通过连续搅拌釜式反应器控制系统来探讨在计算机上实现 MASON 增益公式的方法,利用这种方法编制的 FORTRAN 程序可以用来求解信号流图两点间的总传输或数学关系式。程序在HP-1000机上调试通过。     

一种机器人导航中自然路标的匹配与跟踪方法

提出了一种基于SIFT和KLT算法的自然路标匹配与跟踪方法。该方法利用SIFT算子提取图像中自然路标的特征点集作为模板,然后将机器人采集图像中的SIFT特征点集与模板特征点集进行匹配,获取二者之间仿射关系,并解算自然路标在视野中的位置,为机器人自定位提供参考信息。机器人在运行过程中,将KLT算法与SIFT算法相结合对成功匹配的自然路标进行跟踪,较好地解决了SIFT算法效率低下的问题。实验结果表明该方法对自然路标具有较好的匹配和跟踪效果。     

基于FPSO的小天体着陆系统陆标选取方法

针对用于视觉导航计算的陆标点存在数据量大,计算机存储空间有限的问题,采用一种模糊逻辑规则的粒子群算法的陆标选取方法,并对惯性权值采用模糊逻辑规则方法进行动态调整,以提高算法的求解精度,以空间几何精度因子为适应度指标,建立惯性测量单元、光学相机及测速敏感器多信息融合的小天体探测器着陆系统,最后以Eros433小天体着陆为...     

加权PageRank改进地标表示的自编码谱聚类算法

针对传统谱聚类算法在处理大规模数据集时,聚类精度低并且存在相似度矩阵存储开销大和拉普拉斯矩阵特征分解计算复杂度高的问题。提出了一种加权PageRank改进地标表示的自编码谱聚类算法,首先选取数据亲和图中权重最高的节点作为地标点,以选定的地标点与其他数据点之间的相似关系来逼近相似度矩阵作为叠加自动编码器的输入。然后利用聚类损失同时更新自动编码器和聚类中心的参数,从而实现可扩展和精确的聚类。实验表明,在几种典型的数据集上,所提算法与地标点谱聚类算法和深度谱聚类算法相比具有更好的聚类性能。     

文字输入测试软件的开发

文字输入测试软件主要用于对学习者的文字输入速度和准确度进行测试，本文分析一个文字输入测试软件的系统结构及实现方法，并对应用Delphi编写的此软件的技术要点和编程技巧进行简要的阐述。     

3D face reconstruction and dense alignment with a new generated dataset

Face alignment and reconstruction are classical problems in the computer vision field, one of the greatest difficulties of which is the limited number of facial images with landmark points. The 300 W-LP dataset is the most commonly used for the existing methods of single-view 3D Morphable Model (3DMM)-based reconstruction; however, the model performance is limited by the small variety of facial images in this dataset. In this work, a 3D facial image dataset with landmark points generated by the rotate-and-render method is proposed. The key innovation of the proposed method is that the back-and-forth rotation of faces in 3D space and then re-rendering them to the 2D plane can provide strong self-supervision. The recent advances in 3D face modeling and high-resolution generative adversarial networks (GANs) are leveraged to constitute the blocks. To obtain more precise facial landmark points, the 3D dense face alignment (3DDFA) model is used to label the generated images and filter the landmark points. Finally, the 3DDFA model is retrained using the proposed dataset, and an improved result is achieved.     

A microprocessor-based system for digitizing seismic events from magnetic-tape recordings

The task of converting analogue recordings of seismic events into digital form for computer input can be rendered faster and more reliable than hand-tracing on a digitizing table by the use of a simple microprocessor-based automatic system. We describe the circuitry and software of a system which takes 4 sec to digitize an event and 40 min to punch a card-deck containing 4096 data points; hand-tracing the same record on a digitizing table takes 8 hr. In addition, the automatic system removes the needs of correcting for duplicate points and axis alignment, and of interpolating to obtain equispaced data points. The system, as described, has been configured at minimal cost for input to an outdated mainframe facility; it demonstrates that microprocessor technology can be used to produce time- and labour-saving gains.     

Automatic localization of craniofacial landmarks for assisted cephalometry

In this paper we propose a system for localization of cephalometric landmarks. The process of localization is carried out in two steps: deriving a smaller expectation window for each landmark using a trained neuro-fuzzy system (NFS) then applying a template-matching algorithm to pin point the exact location of the landmark. Four points are located on each image using edge detection. The four points are used to extract more features such as distances, shifts and rotation angles of the skull. Limited numbers of representative groups that will be used for training are selected based on k-means clustering. The most effective features are selected based on a Fisher discriminant for each feature set. Using fuzzy linguistics if-then rules, membership degree is assigned to each of the selected features and fed to the FNS. The FNS is trained, utilizing gradient descent, to learn the relation between the sizes, rotations and translations of landmarks and their locations. The data for training is obtained manually from one image from each cluster. Images whose features are located closer to the center of their cluster are used for extracting data for the training set. The expected locations on target images can then be predicted using the trained FNS. For each landmark a parametric template space is constructed from a set of templates extracted from several images based on the clarity of the landmark in that image. The template is matched to the search windows to find the exact location of the landmark. Decomposition of landmark shapes is used to desensitize the algorithm to size differences. The system is trained to locate 20 landmarks on a database of 565 images. Preliminary results show a recognition rate of more than 90%.