Unsupervised ground filtering of airborne-based 3D meshes using a robust cloth simulation

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• This work proposes a primitive-oriented cloth simulation method for ground filtering of large-scale 3D meshes from airborne platforms. • This method is not affected by low and unbalanced density distribution of mesh vertices. • This method does not require a coherent noise-free 3D mesh. • This work presents a labeled dataset for ground filtering on 3D meshes. Airborne platforms have been improved in the past decade to provide geographic information systems (GISs) with large-scale 3D geographical information. Objectification of such information organized in meshes is a significant challenge for 3D GISs. The ground filtering of 3D meshes is a key step in meeting this challenge, however, its accuracy is highly affected by negative blunders and unbalanced vertex density. This paper proposes a novel method for differentiating ground geometric primitives from realistic 3D meshes based on a cloth simulation filter. Within the method, the fall of a piece of cloth is simulated on a flipped 3D mesh, and the stationary shape of the cloth is considered to be the fitted ground. Utilizing the spatial continuity of meshes, a collision detection based on bounding volume hierarchy is introduced, making the results independent of vertex density. Further, a collision correction based on the scan line and ray casting is proposed to make it applicable to data with negative blunders. The method is assessed quantitatively and visually over several datasets with different vertex densities, scenes, and noise distributions. Results demonstrate that it is a robust method suitable for different landscapes and is not impacted by vertex density and noise.