Automatic quality assessment and update of road data in sub-urban areas using aerial images

必须定期检查道路数据库，以确保其正确性和完整性，特别是在经常变化的郊区地区。在第一个项目期间，制定了一项战略，以核实郊区的道路数据库，以评估道路数据的正确性。第二个项目期的主题是更新郊区的道路数据库，以进一步确保数据库的完整性。在郊区，由于周围环境复杂，例如树木、阴影和车辆，通常不可能提取出一条完整的道路。在更新阶段，我们将使用在第一个项目阶段制定的道路部分提取策略来获得可靠的道路部分。然后，将相邻的道路部分在本地组装成子图。上下文对象用于解释道路部分之间的间隙。将道路部分组装成子图后，必须将它们链接在一起并连接到现有的数据库Roads，以形成道路网。由于郊区公路网的典型结构，全局优化在这里是不切实际的。因此，我们将采用更本地化的方法，建立可以连接子图的连接假设，并使用上下文对象验证它们。

Road databases have to be checked regularly to ensure their correctness and completeness, especially in suburban areas due to frequent changes. In the first project period a strategy for the verification of a road database in suburban areas was developed to assess the correctness of the road data. The topic for the second project period is the update of a road database in suburban areas, to additionally ensure the completeness of the database. In suburban areas it is often not possible to extract a road as a whole due to the complex surroundings, for example trees, shadows, and vehicles. In the update phase, we will use the road part extraction strategy developed in the first project period to obtain reliable road parts. Neighbouring road parts are then assembled locally to subgraphs. Context objects are used to explain the gaps between road parts. After assembling the road parts to subgraphs, they must be linked together and connected to the already existing database roads to form a road network. Due to the typical structure of road networks in suburban areas, a global optimisation is impractical here. Therefore, we will pursue a more local approach, setting up junction hypotheses that can connect the subgraphs and verifying them using context objects.