Abstract
Over the last 20 years the demand for three dimensional (3D) building models has resulted in a vast amount of research being conducted in attempts to automate the extraction and reconstruction of models from airborne sensors. Recent results have shown that current methods tend to favour planar fitting procedures from lidar data, which are able to successfully reconstruct simple roof structures automatically but fail to reconstruct more complex structures or roofs with small artefacts. Current methods have also not fully explored the potential of recent developments in digital photogrammetry. Large format digital aerial cameras can now capture imagery with increased overlap and a higher spatial resolution, increasing the number of pixel correspondences between images. Every pixel in each stereo pair can also now be matched using per-pixel algorithms, which has given rise to the approach known as dense image matching. This paper presents an approach to 3D building reconstruction to try and overcome some of the limitations of planar fitting procedures. Roof vertices, extracted from true-orthophotos using edge detection, are refined and converted to roof corner points. By determining the connection between extracted corner points, a roof plane can be defined as a closed-cycle of points. Presented results demonstrate the potential of this method for the reconstruction of complex 3D building models at CityGML LoD2 specification.
Highlights
The demand for three dimensional (3D) building models has increased over the last two decades, for applications such as asset management, energy modelling and navigation
The methodology develops on the theory of scan line segmentation (Jiang and Bunke, 1994) and run graph vectorisation (Montero et al, 2009) to refine the detected edges before converting the edges into points to form a network of ridgeline connectivity
The inclusion of the normalised DSM (nDSM) boundary has the effect of duplicating detected roof boundary edges, as seen on the right of Figure 3a
Summary
The demand for three dimensional (3D) building models has increased over the last two decades, for applications such as asset management, energy modelling and navigation. Due to the need for up-to-date and readily available 3D models, a vast research effort has focussed on developing an automated workflow for 3D building reconstruction. The success of such approaches is often assessed through the level of detail and accuracy achieved, as defined by the Open Geospatial Consortium (OGC) CityGML standard (Gröger and Plümer, 2012). 3D building models can be simplified by modelling the roof as a flat roof, defined by LoD1 These simple 3D shapes can be reconstructed automatically by applying a single, constant height to building footprints. Examples of this include Ordnance Survey (OS) MasterMap Topography Layer - Building Height Attributes for the UK, and the Dutch Kadaster, which offers countrywide LoD1 building models of the Netherlands (Ordnance Survey, 2014a; Stoter et al, 2014)
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