Visualizing Occupancy Grids, Meshes and Point Clouds using Blender and Python

Obtaining high-quality visualizations of 3D data such as triangular meshes or occupancy grids, as needed for publications in computer graphics and computer vision, is difficult. In this article, I want to present a GitHub repository containing some utility scripts for paper-ready visualizations of meshes and occupancy grids using Blender and Python.

Figure 1 (click to enlarge): Visualization examples of an occupancy grid (left) and a mesh (right) of a chair. The right visualization also shows a point cloud observation (in red).

Blender is an open-source "3D creation suite" — a tool for creating and manipulating 3D shapes and scenes. While I found Blender itself to have a rather steep learning cruve, it does provide a quite extensive Python interface called bpy. For our CVPR'18 and IJCV'20 papers, I used bpy to visualize occupancy grids, meshes and point clouds, see Figure 1. The code, including documentation and examples, is available on GitHub:

Blender Tools on GitHub
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