共查询到20条相似文献,搜索用时 15 毫秒
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空间序列影像共面条件的非量测相机标定方法 总被引:1,自引:0,他引:1
针对非量测相机应用于摄影测量和计算机视觉中存在畸变较大、内方为元素未知等问题,该文为了提高相机标定的灵活性和稳健性,根据立体像对间各同名光线相交的共面条件,推导了顾及6个相机参数和5个相对方位元素共计11个参数的共面条件方程线性化表达式,设计了利用空间序列影像共面条件的非量测相机标定方法。该方法无需外部标定物,可在标定相机参数的同时,解算出各相邻影像之间的相对方位元素值。采用由无人机获取的空间序列影像进行了非量测相机标定实验,得到了与标准检校场一致的标定结果,验证了本文方法的有效性。 相似文献
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针对三维控制场相机检校中像点坐标的量测精度和效率较低的问题,该文研究在三维控制场物方控制(编码)点三维坐标已知的情况,通过对编码点自动识别与定位,借助直接线性变换(DLT)方法计算影像投影变换参数,实现影像控制点像点坐标自动初定位。通过边缘检测、最小二乘椭圆拟合、最小二乘直线拟合等步骤,实现控制点像点坐标的高精度定位量测。试验表明,此方法可实现控制点像点坐标全自动高精度定位量测,定位精度达0.04像元,提高了相机检校的精度和效率。 相似文献
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针对机载LiDAR数据处理中IMU安置角误差检校问题,该文提出一种基于共面约束的自动检校方法。从激光点云中自动提取尖顶房屋顶平面,并建立连接平面关系,基于激光脚点坐标计算公式和共面约束条件,通过平差解算得到IMU安置角误差参数。以Riegl Q780获取的数据进行实验,该方法检校结果与RiProcess软件提供的检校参数非常接近。经过误差改正后,相邻航线获取的点云可以很好地重合在一起。相对于人工选择特征地物进行IMU安置角误差检校,该方法可以大大提高检校的效率和可靠性。 相似文献
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Exactly capturing three dimensional (3D) motion information of an object is an essential and important task in computer vision, and is also one of the most difficult problems. In this paper, a binocular vision system and a method for determining 3D motion parameters of an object from binocular sequence images are introduced. The main steps include camera calibration, the matching of motion and stereo images, 3D feature point correspondences and resolving the motion parameters. Finally, the experimental results of acquiring the motion parameters of the objects with uniform velocity and acceleration in the straight line based on the real binocular sequence images by the mentioned method are presented. 相似文献
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ZHANG Jianqing ZHANG Chunsen HE Shaojun 《地球空间信息科学学报》2006,9(1):32-37
Introduction Amongexistingvisionmoniteringandtheesti mationof3Dmotion,nearlyallinvestigations aremoniteringandtracingthemotionobject basedonsinglesequenceimages.Themotionin formationbyanalyzingthesinglesequenceima gesisrelative,whichincludesascaleoffactor… 相似文献
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在获取广域范围雷达遥感正射影像图时,需要对区域内每景SAR影像进行几何参数修正,提高SAR影像的定位精度。但在广域范围进行控制点的选取和影像的逐一修正,其工作量巨大,严重影响了SAR影像分析应用的效率。对此,本文提出了一种广域范围联合几何检校方法。该方法在R-D模型的基础上,首先利用少许SAR影像计算其独立的系统级检校参数,其次去除系统级检校参数中大气延迟分量的影响,然后依据最小二乘平差原理获取最优的系统级检校参数,最后利用最优的系统级检校参数对所有SAR影像进行几何检校处理。论文采用覆盖中国中东部地区的32景GF-3SAR影像进行联合几何检校试验,检校后的SAR影像定位中误差优于9 m。试验结果表明:该方法能够提高GF-3 SAR影像几何检校的精度,验证了其有效性和可行性。 相似文献
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针对车载移动测量系统中激光扫描仪和载体坐标系之间存在的位置和姿态偏差,在结合常规特征点、特征面检校方法基础上,本文提出了一种带有误差改正数的位置和姿态检校方法。利用TLS获取的车载系统整体点云模型和传感器固有几何属性,获取传感器之间相对关系初值,在此基础上引入误差改正数,构建误差改正模型。在与IGS站联测的检校场中借助平面、球形标靶和平面反射标志等特征,采用最小二乘法迭代法计算误差改正数最优解,从而实现传感器快速检校。试验结果表明,该方法切实可行,检校后点云平面绝对精度和高程绝对精度分别为0.043、0.072 m,相对精度为0.018 m,满足移动测量系统数据获取的精度要求,对促进车载移动测量技术发展和应用具有重要意义。 相似文献
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Hanjiang Xiong Wei Ma Jianya Gong Douadi Abdelalim 《International Journal of Digital Earth》2019,12(5):525-543
Realistic texture mapping and coherent up-to-date rendering is one of the most important issues in indoor 3-D modelling. However, existing texturing approaches are usually performed manually during the modelling process, and cannot accommodate changes in indoor environments occurring after the model was created, resulting in out-dated and misleading texture rendering. In this study, a structured learning-based texture mapping method is proposed for automatic mapping a single still photo from a mobile phone onto an already-constructed indoor 3-D model. The up-to-date texture is captured using a smart phone, and the indoor structural layout is extracted by incorporating per-pixel segmentation in the FCN algorithm and the line constraints into a structured learning algorithm. This enables real-time texture mapping according to parts of the model, based on the structural layout. Furthermore, the rough camera pose is estimated by pedestrian dead reckoning (PDR) and map information to determine where to map the texture. The experimental results presented in this paper demonstrate that our approach can achieve accurate fusion of 3-D triangular meshes with 2-D single images, achieving low-cost and automatic indoor texture updating. Based on this fusion approach, users can have a better experience in virtual indoor3-D applications. 相似文献
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Three-dimensional (3D) reconstruction and texture mapping of buildings or other man-made objects are key aspects for 3D city landscapes. An effective coarse-to-fine approach for 3D building model generation and texture mapping based on digital photogrammetric techniques is proposed. Three video image sequences, two oblique views of building walls and one vertical view of building roofs, acquired by a digital video camera mounted on a helicopter, are used as input images. Lidar data and a coarse two-dimensional (2D) digital vector map used for car navigation are also used as information sources. Automatic aerial triangulation (AAT) suitable for a high overlap image sequence is used to give initial values of camera parameters of each image. To obtain accurate image lines, the correspondence between outlines of the building and their line features in the image sequences is determined with a coarse-to-fine strategy. A hybrid point/line bundle adjustment is used to ensure the stability and accuracy of reconstruction. Reconstructed buildings with fine textures superimposed on a digital elevation model (DEM) and ortho-image are realistically visualised. Experimental results show that the proposed approach of 3D city model generation has a promising future in many applications. 相似文献