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Automatic 3D-reconstruction of buildings using highly resolving video sequences

Automatic 3D-reconstruction of buildings using highly resolving video sequences
使用高分辨率视频序列自动 3D 重建建筑物
批准号:
62030896
负责人:
Professor Dr.-Ing. Olaf Hellwich
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2007
资助国家:
德国
项目状态:
已结题
起止时间:
2006-12-31 至 2010-12-31

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中文摘要
翻译
在最后一个阶段,我们成功地开发了一个原型系统,用于使用地面图像数据生成城市三维地理信息系统的建筑模型。这个全自动化系统的一个特点是其输入和输出数据的高度冗余。到目前为止,这处房产只被部分开发过。因此,我们希望利用密集空间匹配和稀疏时间跟踪相结合的技术来提高扩展摄像机漂移的运动恢复和重建质量。几个自动选择的代表点将存储在八叉树数据结构中,并用作3D场景的控制网格。这些点允许系统确定用于位姿估计、对象重建和误差最小化的最佳三角测量条件。此外,我们希望扩展我们现有的系统,为每个3D点提供质量测量。弱测量部分可以在视频序列中以更高的精度重现。这些相同的部分由上述代表点检测,并通过选择适当的权重来提高全局精度。重建的立面包含了与汽车、树木和街道照明等遮挡对象之间的间隙。由于我们有大量的冗余数据,我们可以自动填补漏洞。关键的任务是分离被遮挡的部分,并将点云与其他重建相结合。此外,必须使用运动分割来检测非刚性对象,以防止不一致。最后,我们希望在现有的地理信息系统数据库中集成几个不同比例尺的重建。
英文摘要
In the last period we successfully developed a prototype system to generate building models for an urban 3D GIS using terrestrial image data. One attribute of this fully automated system is its high redundancy of input and output data. This property has only been partially exploited so far. Therefore, we want to improve the egomotion recovery for extended camera excursions and the reconstruction quality using the integrated techniques of dense spatial matching and sparse temporal tracking. Several automatically selected representative points will be stored in an octree data structure and used as a control grid for the 3D scene. These points allow the system to determine optimal triangulation conditions for pose estimation, object reconstruction and error minimization. Furthermore, we want to extend our existing system with a quality measure for every 3D point. Weakly measured parts can reappear during the video sequence with better accuracy. These identical parts are detected by the representative points described above and enhance the global accuracy by selection of appropriate weights. The reconstructed fa?ade contains gaps from occluding objects like cars, trees and street lighting. Due to our large amount of redundant data we can fill up holes automatically. The critical task is to separate occluded parts and integrate point clouds from other reconstructions. Additionally, non-rigid objects must be detected using motion segmentation to prevent inconsistencies. Finally, we want to integrate several reconstructions with varying scales in an existing GIS database.
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  • 财政年份:
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