| Popis: |
3D point clouds represent an essential category of geodata used in a variety of geoinformation applications and systems. We present a novel, interactive out-of-core rendering technique for massive 3D point clouds based on a layered, multi-resolution kd-tree, whereby point-based rendering techniques are selected according to each point’s classification (e.g., vegetation, buildings, terrain). The classification-dependent rendering leads to an improved visual representation, enhances recognition of objects within 3D point cloud depictions, and facilitates visual filtering and highlighting. To interactively explore objects, structures, and relations represented by 3D point clouds, our technique provides efficient means for an instantaneous, ad hoc visualization compared to approaches that visualize 3D point clouds by deriving mesh-based 3D models. We have evaluated our approach for massive laser scan datasets of urban areas. The results show the scalability of the technique and how different configurations allow for designing task and domain-specific analysis and inspection tools. |
