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The introduction of 3D scanning has strongly influenced environmental sciences. If the resulting point clouds can be transformed into polygon meshes, a vast range of visualisation and analysis tools can be applied. But extracting accurate meshes from large point clouds gathered in natural environments is not trivial, requiring a suite of customisable processing steps. We present Habitat3D, an open source software tool to generate photorealistic meshes from registered point clouds of natural outdoor scenes. We demonstrate its capability by extracting meshes of different environments: 8,800 m2 grassland featuring several Eucalyptus trees (combining 9 scans and 41,989,885 data points); 1,018 m2 desert densely covered by vegetation (combining 56 scans and 192,223,621 data points); a well-structured garden; and a rough, volcanic surface. The resultant reconstructions accurately preserve all spatial features with millimetre accuracy whilst reducing the memory load by up to 98.5%. This enables rapid visualisation of the environments using off-the-shelf game engines and graphics hardware.
|Number of pages||13|
|Journal||Environmental Modelling and Software|
|Early online date||27 Oct 2017|
|Publication status||E-pub ahead of print - 27 Oct 2017|
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- 1 Finished
Exploiting invisible cues for robot navigation in complex Natural environments
28/02/15 → 31/08/18