3D Python
Python Tutorial for Euclidean Clustering of 3D Point Clouds with Graph Theory. Fundamental concepts and sequential workflow for unsupervised segmentation.
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Aside from sounding cool, why do I take three weeks off to write a Python tutorial on graph theory for 3D data?
The short answer is that it is extremely useful for understanding 3D scenes. It can transform how efficiently you process 3D datasets for decision-making scenarios.
But there are many challenges to be aware of.
If we take a step back, our eyes can capture spatial information and then process it through our cognition system. And this is where the magic lies: our brain helps us make sense of the scene and its relational decomposition.
With internal knowledge representation, you can instantly know that your scene is made of floors and walls, that the floor hosts chairs and tables, and that, in turn, the cup, microwave, and laptop stand on the desks.