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Efficient representation and generation of consistent 3D and 4D maps

高效表示和生成一致的 3D 和 4D 地图

基本信息

批准号：
200549750
负责人：
Professor Dr. Reinhard Klein
金额：
--
依托单位：
Institut für Informatik
依托单位国家：
德国
项目类别：
Research Units
财政年份：
2011
资助国家：
德国
起止时间：
2010-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/200549750?language=en
关键词：
Efficient representation generation consistent 3D

项目摘要

The aim of P6 is the development of data structures and algorithms that can manage large amounts of 3D data. This should allow for both quick access to relevant parts of the data for the calculation of occupancy maps and the visualization and at the same time also support efficient insertion, deletion, and completion of the data. At the same time data recorded at different times should be identifiable persistently maintained in the system. The key to achieve this goal is on the one hand the application of out-of-core approaches and on the other hand the use of compression algorithms. Therefore, we will extend the developed compression methods in order to support time varying versions of the raw data by a persistent representation. The efficient upgradeability and the multi-resolution capability of the representation should be guaranteed.In addition methods for procedural description of surface structures of buildings will be investigated and exploited to improve the compression rates. As has already been demonstrated in experiments in phase I, current methods for geometry compression are not able to handle rough surfaces, such as plaster, clinker, or on finer scales also wallpapers, since these structures constitute a major part of the entropy of the data to be compressed. We aim for representing these structures by procedural noise models, rather than to compress them. Having found the relevant parameters of a suitable procedural noise model statistical analysis of the data allows for the determination of anomalies such as cracks or other irregularities in the masonry. Furthermore, a surface with the same statistical characteristic can be reproduced from the compressed smoothed underlying geometry and the procedural noise model. The third focus of the subproject will be on methods for robust and efficient symmetry detection on rough scales which serves several purposes. Firstly, it helps in the production of occupancy maps, which for obstacle avoidance (P2/P3) are required. On the other hand, it facilitates the action generation at the autonomous exploration (P8). In addition, they will also improve the geometry compression further, since self-similarity can be detected and used on coarse scales already. Finally, discovered self-similarities can also be used for meaningful supplement or completion of geometry data, which can, if necessary, avoid multiple overflights of an object. Typical examples are bays or towers that appear more than once in the overall building and usually have to be captured from several sides. To this end, the primitive-based reconstruction method for point clouds co-developed by one of the applicants will first be integrated into the reconstruction methods of P5 and second be extended to symmetric subparts that can be detected in the point cloud.

P6的目标是开发可以管理大量3D数据的数据结构和算法。这应该允许快速访问数据的相关部分以计算占用图和可视化，并且同时还支持数据的有效插入、删除和完成。同时，在不同时间记录的数据应该是可识别的，并持久地保存在系统中。实现这一目标的关键是一方面应用核外方法，另一方面使用压缩算法。因此，我们将扩展开发的压缩方法，以支持时变版本的原始数据的持久表示。此外，还将研究和开发建筑物表面结构的过程化描述方法，以提高压缩比。正如在第一阶段的实验中已经证明的那样，当前的几何压缩方法不能处理粗糙的表面，例如石膏、熟料，或者在更精细的尺度上也不能处理壁纸，因为这些结构构成了要压缩的数据的熵的主要部分。我们的目标是通过程序噪声模型来表示这些结构，而不是压缩它们。在找到合适的程序噪声模型的相关参数后，数据的统计分析允许确定异常，例如砌体中的裂缝或其他不规则性。此外，具有相同统计特性的表面可以从压缩的平滑的底层几何形状和程序噪声模型中再现。该分项目的第三个重点将是在粗略尺度上进行稳健和有效的对称性检测的方法，这有几个目的。首先，它有助于生成占用地图，这是避障（P2/P3）所必需的。另一方面，它有助于自主探索（P8）的动作生成。此外，它们还将进一步改善几何压缩，因为自相似性已经可以在粗略尺度上检测和使用。最后，发现的自相似性也可以用于有意义的补充或完成的几何数据，这可以在必要时，避免一个对象的多次飞越。典型的例子是海湾或塔楼，它们在整个建筑中出现不止一次，通常必须从几个侧面捕捉。为此，由其中一位申请人共同开发的基于基元的点云重建方法将首先集成到P5的重建方法中，然后扩展到可以在点云中检测到的对称子部分。