首页> 外文学位 >Object space matching and reconstruction using multiple images.
【24h】

Object space matching and reconstruction using multiple images.

机译:使用多个图像进行对象空间匹配和重建。

获取原文
获取原文并翻译 | 示例

摘要

Extraction of man-made objects from imagery hall ear an active research area in photogrammetry and computer vision societies for decades, and feasible solution for simple structures have been reported and showed success on rural scenes As one of the important map compolnents of man-made objects, automatic extraction, or less human intervention, of them has great impacts on relieving the bottle neck of data-to-information workflow and generating city models/planning/monitoring applications.;When it comes to reconstruction of urban scenes, matching and reconstruction find difficulties with conventional methods, since linear features which are rich in urban scenes and suitable for describing man-made objects are not matching and reconstruction entities in conventional point based photogrammetry. Meanwhile feature-based photogrammetry claiming geometric strength, accuracy in measurements and ability to fuse with other sensor data has showed potential for effective treatment of linear features However, notable progress, to use linear features has been made in orientation to solve camera calibration and viewing geometry.;This research attempts to fill the gaps which are at their early stages - matching intersection and groupings of linear features in feature based photogrammetry The study first focuses on the fullest investigation of geometric constraints made by camera viewing geometry and prior knowledge Then novel geometry-driven line matching in object space which does not use photometric information and is suitable for multiple image configuration is presented. Moreover, matching takes specifically vertical horizontal arbitrary line and orthogonal junction to provide benefits for reconstruction with explicit information. Proximity, parallelism perpendicularity applied to group matched lines, and reconstruction is completed by detecting and adding missing but critical line entities. The output results in three different man-made structures - building complex, C-shaped single building with roof and single building with structures, that show feasible solutions in resolving complementing and alleviating (1) the limitation of existing matching methods in urban scenes and (2) the limitation in accommodating linear features in matching. Furthermore output in reconstruction showed that man-made objects can be well-described by lines and junctions which are matching and reconstruction entities in this study.
机译:几十年来,从照相厅耳中提取人造物体成为摄影测量学和计算机视觉社会的活跃研究领域,并且已经报道了针对简单结构的可行解决方案,并在农村场景中显示出成功作为人造物体的重要地图成分之一,自动提取或较少的人工干预,对减轻数据到信息工作流程的瓶颈以及生成城市模型/规划/监视应用程序都将产生重大影响。在重建城市场景时,需要进行匹配和重建传统方法存在困难,因为在传统的基于点的摄影测量中,丰富的城市景观和适合于描述人造物体的线性特征不匹配,无法重建实体。同时,声称具有几何强度,测量精度以及与其他传感器数据融合能力的基于特征的摄影测量法显示了对线性特征进行有效处理的潜力。然而,在定向上使用线性特征解决相机校准和查看几何结构方面取得了显着进展。;这项研究试图填补处于早期阶段的空白-在基于特征的摄影测量中匹配相交点和线性特征的分组。研究首先集中于对照相机观看的几何形状和先验知识进行的几何约束的最充分研究,然后研究新颖的几何形状-提出了不使用光度信息且适用于多图像配置的对象空间中的驱动线匹配。此外,匹配采用特定的垂直水平任意线和正交结,从而为使用显式信息进行重构提供了好处。接近度,平行度垂直度应用于组匹配的线,并通过检测并添加缺失但关键的线实体来完成重建。输出结果是三种不同的人造结构-建筑复杂的C形带屋顶的单幢式建筑物和带结构的单幢式建筑物,显示出解决补充和缓解(1)城市场景中现有匹配方法的局限性和( 2)在匹配中容纳线性特征的限制。此外,在重建中的输出表明,人造对象可以由匹配和重建实体的线和连接点很好地描述。

著录项

  • 作者

    Ahn, Yushin.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Geology.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 126 p.
  • 总页数 126
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:38

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号