A software system for efficient DEM segmentation and DTM estimation in complex urban areas

Digital Elevation Models (DEMs) are a central information source for scene analysis, including specific tasks such as building localization and reconstruction. Whatever application is envisaged, DEM segmentation is a critical step, due to the great variability of landscapes and above-ground structures in urban areas. Moreover, a DEM may contain erroneous isolated 3D points which have to be identified before any interpretation process can start. Designing an automatic DEM segmentation method that is successful under all circumstances can hardly be envisaged. To facilitate the segmentation process, a user-friendly, interactive software environment, called ReconLab, has been developed. Its 3D viewing and editing capabilities allow to easily detect and remove erroneous 3D points from the initial data, to efficiently smooth the DEM and perform the segmentation in real time. ReconLab's usefulness for urban scene interpretation is demonstrated by applying it to the estimation of a Digital Terrain Model (DTM) from the DEM. In particular, Recon-Lab is used to perform a fast, semi-automatic segmentation of the DEM and to provide a significant and representative sample region consisting of ground points. These points are then used to initialize a parametric model for the terrain, which is iteratively refined by a robust algorithm. The preprocessing by ReconLab reduces computation time by a factor 3, without loss of accuracy, as is demonstrated by experiments on synthetic data and on real world DEMs obtained by airborne laser altimetry as well as by stereo correspondence from imagery.