Abstract
Voxel representations have been used for years in scientific computation and medical imaging. The main focus of our research is to provide easy access to methods for making large-scale voxel models of built environment for environmental modelling studies while ensuring they are spatially correct, meaning they correctly represent topological and semantic relations among objects.In this article, we present algorithms that generate voxels (volumetric pixels) out of point cloud, curve, or surface objects. The algorithms for voxelization of surfaces and curves are a customization of the topological voxelization approach [1]; we additionally provide an extension of this method for voxelization of point clouds.The developed software has the following advantages:•It provides easy management of connectivity levels in the resulting voxels.•It is not dependant on any external library except for primitive types and constructs; therefore, it is easy to integrate them in any application.•One of the algorithms is implemented in C++ and C for platform independence and efficiency.
Highlights
We present three methods for voxelating point, curve, and surface objects
The algorithms for voxelization of surfaces and curves are a customization of the topological voxelization approach [1]; we provide an extension of this method for voxelization of point clouds
License: Our software is licensed under the Apache License Version 2.0 (APLv2)
Summary
The C++ and C version of our libraries requires the input to be stored in OBJ format, some examples are provided under: https://github.com/NLeSC/geospatial-voxels/tree/master/software/voxelGen/ data. Rhinoceros3D1 and Grasshopperß, NURBS Modelling for Windows (Windows 7 or higher) with Dot NET framework (version 3.5 or higher) to run C# version. The codes have been tested with PC 64-bit machines with Intel (R) i7 Core(TM) CPU@ 2.50 GHz and installed memory (RAM) of 8 GB. Link: https://github.com/NLeSC/geospatial-voxels/tree/master/software/voxelGen. License: Our software is licensed under the Apache License Version 2.0 (APLv2). The methods and algorithms can be reused, adapted and integrated with software applications that require voxelization. The installation steps are described in GitHub
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