From time to time, I like playing with 3D graphics, especially from a programmer’s point of view.

Constructive solid geometry, or CSG, is a modeling technique involving combining simpler objects with Boolean operations to obtain more complex ones.

A while ago, I found an implementation as a JavaScript library: CSG.js.

It really is brilliant because it is a complete tool in less than 600 rows, half of which are explanatory comments.

Its foundations are the clipping and the inversion operation. The former removes parts of a BSP tree inside another BSP tree, the latter swaps solid and empty space.

CSG.js combines them cleverly to implement Boolean union, subtraction, and intersection.

Even from a software engineering perspective, its author made some acute choices. And as a result, this project did not need to be updated in the latest ten years!

For example, library users can implement vertices with custom properties thanks to duck typing. They just need to implement a few methods and have a pos member. In this way, it is possible, for instance, to manage texture coordinates. … [Leggi il resto]

For my Master’s degree thesis, I dove into acquiring static objects with a RGBD sensor. Eventually, I decided to use the Kinect Fusion algorithm, which produced decent results.

I found this topic fascinating, so I continued on my own, but in another direction: acquiring people. So, in the last few months, I have been experimenting with scanning myself and my friends with a Microsoft Kinect One.

Conditioned by my previous results, initially, I tried with point clouds.

Deformation graph approach

One approach I found in several papers consists in:

1. acquiring only a few scans (from 6-8 points of view), with the person as still as they can;
2. performing a rough global alignment;
3. running ICP to improve the rigid alignment locally;
4. downsampling the point cloud to build a deformation graph;
5. resolving an optimization problem;
6. deforming the denser point clouds.

Reaching point 3 is not trivial because people move. ICP can be very unforgiving, and in some cases, you also need some luck to obtain good results at this stage.

For downsampling (Point 4), I used Open3D’s voxelization followed by averaging point coordinates. I do not know how this can influence the final results compared to something like a clustering algorithm. … [Leggi il resto]