基于多片前方交会的工业摄影测量自动匹配

针对数字工业摄影测量中的人工标志点的快速自动匹配问题,根据从物方空间角度描述核线的原理,提出了一种基于空间前方交会的匹配算法。该算法首先通过计算投影线间的最短距离来确定一组初始匹配像点;然后通过双片空间前方交会来确定一组潜在的物方点,并将其按距离分组;最后,将每一个潜在的物方点的坐标残差过大及属于同一张像片的像点剔除,同时通过判断与各物方点对应的像点数来确定同名像点。两组实验均证明,该算法不仅计算速度快,而且具有高匹配率和低误匹配率,能为数字工业摄影测量自检校光束法平差提供高精度的初值。     

动态优化不等精度经纬仪交会方法

在多台不等精度经纬仪交会测量系统中,为提高数据的可靠性和精度,根据异面交会原理,提出空间定位精度及其误差的模型;提出采用定常异动算子算法和普通加权平均法相结合的处理方法;对该算法进行数学仿真,计算分别使用定常异动算子和普通加权平均法的交会角区间,并在实际任务中加以应用。试验结果表明,采用合理的算法对多台不等精度经纬仪进行交会测量,增加了测量基线数量从而提高了整体数据的稳定性,同时提高了测量精度。     

虚拟CCD线阵星载光学传感器内视场拼接

以基于虚拟CCD线阵的多CCD影像重成像算法作为内视场拼接的技术手段,在对由地形起伏引起的多CCD影像的拼接误差进行理论分析和推导的基础上,提出无需数字高程模型(DEM)的虚拟CCD线阵多CCD影像重成像算法;并提出使用基于严密成像几何模型的空间前方交会的方法直接评价影像拼接对摄影测量生产的精度影响。研究表明,在虚拟CCD"安装"位置与真实CCD位置偏差不大的情况下,使用成像区域的平均高程进行拼接即可满足几何无缝拼接的需求;而在虚拟CCD"安装"位置与真实位置的偏离超过限差的情况下,可以用航天飞机雷达地形测绘DEM(SRTM-DEM)等一定精度的DEM数据校正地形起伏引起的拼接误差。使用先进陆地观测卫星(ALOS)卫星全色遥感立体测绘仪(PRISM)传感器三线阵影像作为实验数据,对前视、下视和后视的多CCD影像分别进行拼接。对拼接线的判读结果表明,影像拼接效果良好。另外,分别对拼接前和拼接后的前视、后视影像选取同名点进行空间前方交会,拼接后影像的空间前方交会精度与拼接前影像的空间前方交会精度一致。本文方法,可以无需DEM进行ALOS PRISM的内视场拼接,并使得拼接后影像的立体测图精度无损;拼接误差分析方法也可以在航空相机影像拼接中推广。     

基于遗传算法的多台光电经纬仪优化布站研究

利用部署于不同地点的多台光电经纬仪对飞行目标进行交会测量,可以确定被测目标的空间位置.为提高对被测目标的定位精度,提出了一种基于遗传算法的多台光电经纬仪优化布站方法.首先建立了光电经纬仪交会测量定位优化布站数学模型,然后针对该优化问题对遗传算法进行了设计,最后运用该算法对三台光电经纬仪布站几何进行了优化布站仿真计算,得到了三台光电经纬仪经布站优化后的站点坐标,且仿真结果表明该方法能够明显提高对被测目标的定位精度.     

球面全景影像自动测量路灯坐标的方法

目的 针对城市实施的路灯杆编码项目,即获取路灯坐标并依次编号,传统的测量方法耗费大量人力物力,且作业周期长,虽然激光测量精度高,但成本也高。为此本文提出一种将基于深度学习的目标检测与全景量测结合自动获取路灯坐标的方法。方法 通过Faster R-CNN（faster region convolutional neural network）训练检测模型,对全景图像中的路灯底座进行检测,同时输出检测框坐标,并与HOG（histogram of oriented gradient）特征结合SVM（support vector machine）的检测结果进行效果对比。再将检测框的对角线交点作为路灯脚点,采用核线匹配的方式找到两幅图像中一个或多个路灯相对应的同名像点并进行前方交会得到路灯的实际空间坐标,为路灯编码做好前期工作。结果 采用上述两种方法分别对100幅全景影像的路灯进行检测,结果显示Faster R-CNN具有明显优势,采用Faster R-CNN与全景量测结合自动获取路灯坐标。由于路灯底部到两成像中心的距离大小及3点构成的交会角大小对坐标量测精度具有较大影响,本文分别对距离约为7 m、11 m、18 m的点在交会角为0°180°的范围进行量测结果对比。经验证,交会角在30°150°时,距离越近,对量测精度的影响越小。基于上述规律,在自动量测的120个路灯坐标中筛选出交会角大于30°且小于150°,距离小于20 m的102个点进行精度验证,其空间坐标量测结果的误差最大不超过0.6 m,中误差小于0.3 m,满足路灯编码项目中路灯坐标精度在1 m以内的要求。结论 本文提出了一种自动获取路灯坐标的方法,将基于深度学习的目标检测应用于全景量测中,避免手动选取全景图像的同名像点进行双像量测,节省大量人力物力,具有一定的实践意义。本文方法适用于城市车流量较少的路段或时段,以免车辆遮挡造成过多干扰,对于路灯遮挡严重的街道全景,本文方法存在一定的局限性。     

对偶四元数单片空间后方交会算法

将对偶四元数理论引入航空影像的空间后方交会求解中,提出了一种新颖的对偶四元数单片空间后方交会算法。该算法采用对偶四元数描述坐标系之间的旋转和平移,然后对严格的共线条件方程进行线性化,并按照带有约束条件的间接平差进行迭代解算。实验结果证明,该算法的可靠性和稳定性不依赖于影像位置和姿态的初始值,并具有适用于不同的倾角、航高、遥感平台、迭代次数少和定向精度高等优点。     

光测在模型自由飞试验中的应用

主要讨论了采用光测设备测量模型自由飞的轨迹问题.针对模型自由飞的特点,综合利用两台小型激光电视测量系统(OKA)、GPS、全站仪(TCRA1101)等现有设备,设计了安全、可靠的模型自由飞跟踪、测量方案;利用方向余弦交会算法,对测量的模型自由飞数据进行处理,并采用两种不同的方法进行了测量精度检查,结果表明测试精度满足测试要求.     

车载移动测量系统前方交会中的误差分析

车载移动测量系统是由多个传感器集成的系统,定位精度受到很多因素的影响.首先简要介绍了车载摄影测量中内外方位元素的计算方法;其次,针对线性法前方交会求解中符号矩阵的直接求逆内存占用大的问题,提出利用杜利特尔分解(LU分解)的方法,推导出了前方交会的解算公式;最后,针对短基线小交会角的情况利用误差传播定律分析了各误差源对最终定位结果的影响,对于进一步研究车载移动测量系统具有一定的参考意义.     

一种基于平面控制直线约束的非量测相机检校方法

光束法自检校为一种经典的适合于非量测相机的检校算法,但其解算精度易受到大量像点坐标观测值的影响.本文讨论一种基于平面控制直线约束的非量测相机检校方法.该方法利用平面格网控制场中的直线特征对格网像点坐标及畸变参数进行直线几何约束.详细推导了该方法的直线约束方程,对检校实验结果从控制场格网点直线性、构像残差等方面进行分析.经实验验证,相较传统的光束法自检校,该附加直线约束的检校方法可有效提高检校结果精度.     

基于MATLAB的无人飞行器两点交会定位算法研究

空间飞行器现有定位算法采用单点测距测角,定位误差高达上百米。该文提出了空间两点交会定位方法,该方法可有效提高定位精度,并通过MATLAB进行了算法实现,最终编写了定位软件。     

基于序列图像的摄像机自标定方法

提出了一种新的结合摄影测量和计算机视觉相关理论的摄像机自标定方法。首先通过序列图像的匹配点对,利用计算机视觉理论中的8点法求得摄像机基础矩阵F,通过矩阵F利用Kruppa方程求得矩阵C,对矩阵C进行Cholesky分解得到摄像机的内参数矩阵K,然后将求出的内参数作为初始值,利用摄影测量理论进行相对定向和绝对定向,最小二乘前方交会计算得到匹配点对的三维空间坐标,最后由匹配点对的三维空间坐标及其图像坐标,采用三维直接线性变换和光束法平差方法解算出摄像机内、外参数及畸变系数。该方法不依赖于特定的场景几何约束条件,只要序列图像之间有匹配点对,就可以进行自标定工作,具有广泛的适用性。模拟数据和真实图像的实验结果表明：该方法计算过程简单,标定精度高,是一种值得借鉴的摄像机自标定方法。     

Deformation visual inspection of industrial parts with image sequence

A new approach to reconstructing and inspecting the deformation of industrial parts, especially sheetmetal parts based on CAD-designed data and hybrid point-line bundle adjustment with image sequence, is proposed. Nonmetric image sequence and CAD-designed data of parts are used as the source of information. The strategy of our approach is to reconstruct and inspect deformations of parts automatically with image points and line segments extracted from the images. Basic error equation of line photogrammetry and its modified form are addressed in detail. It is shown that when a certain proper weight is selected, adjustment by condition equations and adjustment by observation equations are equivalent for line photogrammetry. A novel hybrid point-line bundle adjustment algorithm is used to reconstruct industrial parts. The proposed hybrid adjustment model can be used in various 3D reconstruction applications of objects mainly composed of points and lines. The developed inspection system is tested with true image data acquired by a CCD camera, and the results are very satisfying.Received: 27 May 2002, Accepted: 18 September 2003, Published online: 8 June 2004     

强约束条件下环绕式相机标定方法

目的 在计算机视觉和摄影测量领域,经常应用多视角图像对场景进行高精度的三维重建。其中,相机内参数和相机间固定相对关系的高精度标定是关键环节,文章提出一种能够在强约束条件下快速进行相机标定的方法。方法 通过相机间6个相互独立的约束,充分利用系统的几何条件,确定固有关系,再以共线方程为基础推导强约束条件下的平差模型,并应用于自检校光束法平差,开展相邻立体相机的匹配,实现多相机系统的快速标定。结果 最后通过实验,验证了加了强约束条件后,加大了平差的多余观测数,提高了标定精度和鲁棒性。结论 建立了相机标定系统,提出了在强约束条件下快速进行相机标定的方法,展开了人体三维重建研究,并且该方法可推广到多个相机组成的多相机立体量测系统的标定中。     

Characterization for High Dynamic Range Imaging

In this paper we present a new practical camera characterization technique to improve color accuracy in high dynamic range (HDR) imaging. Camera characterization refers to the process of mapping device‐dependent signals, such as digital camera RAW images, into a well‐defined color space. This is a well‐understood process for low dynamic range (LDR) imaging and is part of most digital cameras — usually mapping from the raw camera signal to the sRGB or Adobe RGB color space. This paper presents an efficient and accurate characterization method for high dynamic range imaging that extends previous methods originally designed for LDR imaging. We demonstrate that our characterization method is very accurate even in unknown illumination conditions, effectively turning a digital camera into a measurement device that measures physically accurate radiance values — both in terms of luminance and color — rivaling more expensive measurement instruments.     

A generic structure-from-motion framework

We introduce a generic structure-from-motion approach based on a previously introduced, highly general imaging model, where cameras are modeled as possibly unconstrained sets of projection rays. This allows to describe most existing camera types including pinhole cameras, sensors with radial or more general distortions, catadioptric cameras (central or non-central), etc. We introduce a structure-from-motion approach for this general imaging model, that allows to reconstruct scenes from calibrated images, possibly taken by cameras of different types (cross-camera scenarios). Structure-from-motion is naturally handled via camera independent ray intersection problems, solved via linear or simple polynomial equations. We also propose two approaches for obtaining optimal solutions using bundle adjustment, where camera motion, calibration and 3D point coordinates are refined simultaneously. The proposed methods are evaluated via experiments on two cross-camera scenarios—a pinhole used together with an omni-directional camera and a stereo system used with an omni-directional camera.     

基于平面格网的非量测CCD相机自标定

传统的相机标定方法通常需要建立复杂3维标定块或高精度3维控制场,在实际应用中受到了一定的限制。本文采用平面控制格网作为标定块,根据相机的理想模型确定内方位元素,利用2维直接线性变换和共线方程分解出相机的外方位元素初值,采用改进的Hough变换算法检测标定图像中的格网直线并利用最小二乘法拟合出最佳直线,通过求直线的交点得到标定格网点的像坐标。最后利用自检校光线束法平差进行相机的精确标定。实际图像数据实验结果表明,主点和焦距的标定精度分别达到了0.2像素和0.3像素左右。可以满足高精度近景3维量测的要求。     

Fusion of range camera and photogrammetry: a systematic procedure for improving 3-D models metric accuracy

The generation of three-dimensional (3-D) digital models produced by optical technologies in some cases involves metric errors. This happens when small high-resolution 3-D images are assembled together in order to model a large object. In some applications, as for example 3-D modeling of Cultural Heritage, the problem of metric accuracy is a major issue and no methods are currently available for enhancing it. The authors present a procedure by which the metric reliability of the 3-D model, obtained through iterative alignments of many range maps, can be guaranteed to a known acceptable level. The goal is the integration of the 3-D range camera system with a close range digital photogrammetry technique. The basic idea is to generate a global coordinate system determined by the digital photogrammetric procedure, measuring the spatial coordinates of optical targets placed around the object to be modeled. Such coordinates, set as reference points, allow the proper rigid motion of few key range maps, including a portion of the targets, in the global reference system defined by photogrammetry. The other 3-D images are normally aligned around these locked images with usual iterative algorithms. Experimental results on an anthropomorphic test object, comparing the conventional and the proposed alignment method, are finally reported.     

一种快速的人工场景图像消失点检测方法

人工场景中包含了大量的空间平行线以及垂直边,这些空间平行线映射到图像中相交产生的交点即消失点。消失点检测对摄像机标定、三维场景重建等都有着重要的意义。传统的消失点检测算法往往基于二维霍夫参数空间,复杂度高、效率低。因此,提出一种新的方法,先检测图像中较长的边界线,并将检测到的线段进行筛选、分组;然后利用消失点与焦距之间的制约关系,确定三向消失点的位置以及焦距的大小。该方法将传统的二维霍夫参数空间转换为二级一维霍夫参数空间。实验表明,这种方法运算复杂度低、运行时间短。在室外场景图像中,鲁棒性好,且保持较高的准确率。     

Hybrid Parallel Bundle Adjustment for 3D Scene Reconstruction with Massive Points

Bundle adjustment(BA) is a crucial but time consuming step in 3D reconstruction.In this paper,we intend to tackle a special class of BA problems where the reconstructed 3D points are much more numerous than the camera parameters,called Massive-Points BA(MPBA) problems.This is often the case when high-resolution images are used.We present a design and implementation of a new bundle adjustment algorithm for efficiently solving the MPBA problems.The use of hardware parallelism,the multi-core CPUs as well as GPUs,is explored.By careful memory-usage design,the graphic-memory limitation is effectively alleviated.Several modern acceleration strategies for bundle adjustment,such as the mixed-precision arithmetics,the embedded point iteration,and the preconditioned conjugate gradients,are explored and compared.By using several high-resolution image datasets,we generate a variety of MPBA problems,with which the performance of five bundle adjustment algorithms are evaluated.The experimental results show that our algorithm is up to 40 times faster than classical Sparse Bundle Adjustment,while maintaining comparable precision.