2023-03-06, 12:15–12:45, Auditorium
Mobile Mapping point cloud object detection is becoming vital and essential for many real-world applications when it comes to precisely measure and detect critical objects. The municipality of Rotterdam is responsible for road construction details and maintenances of streets in Rotterdam. For example, the municipality will try to take into account the slope of the street. In this way they ensure that the new street or newly installed elements do not cause any disruption to water drainage.
Mobile Mapping point cloud object detection is becoming vital and essential for many real-world applications when it comes to precisely measure and detect critical objects. The municipality of Rotterdam is responsible for road construction details and maintenances of streets in Rotterdam. For example, the municipality will try to take into account the slope of the street. In this way they ensure that the new street or newly installed elements do not cause any disruption to water drainage. One crucial object that needs to be detected and measured is sill heights. The method that is currently used contains large amount of manual work.
We used mobile mapping point clouds data collected by LiDAR sensors mounted on a moving vehicle. We implemented a practical pipe line workflow of automatically extracting accurate representation of sill heights objects from large amount of point cloud data. In this way, we succesfully designed a verification system to classify detected sill heights objects to ensure that if the sill height on individual detected objects meets the criteria. We used advanced python libraries to automatically detect and classify sill height objects. Our workflow can be used for other type of objects from large amount of point clouds data for the city of Rotterdam and different asset management applications.