Model complexity in ESB

I need to study the complexity of models in the PRECISE engineering shape benchmark (ESB) collection. Although such approximation is not always true, I considered that more complex objects contain more faces, while meshes with less triangles represent simpler models. Indeed, a simpler object might contain more faces than a more complex one, depending on the mesh. However, this is not common in the ESB collection and the face count is easy to estimate. From this estimation, I concluded that the majority of the models in this collection contain more than ten thousand polygons, as illustrated in chart below.

Distribution of models from ESB collection according to face count

Counting faces in STL files

To help me creating statistics on collections of 3D models I developed a small application that counts the faces of models stored in STL files. It can be used to analyze a single model or a collection of models. The first is done by specifying the corresponding STL file and the second by specifying the folder that contains the collection. If you think such application might be useful, you can download the windows binary [ZIP 71KB] or ask me the cross-platform source code.

Output produced by FaceCounter application

CAS name change

From discussions with colleagues from SMG at IMATI-Ge, we concluded that the name originally given to the decomposition algorithm was not the most appropriate. Indeed, it might lead to some confusion and misinterpretation. Therefore, we decided to change the algorithm name to "Collection-Aware Segmentation".

Goodbye Genoa

My fellowship at CNR IMATI-Ge finished last Friday. Thus, on Saturday morning I was packing and in the afternoon embarking on a ferry to Barcelona, from where I rode to Lisbon.

I want to thank everybody at the Shape Modeling Group for the way they welcomed and supported me: it was a pleasure to work with you, guys.

Waiting, with other motorcyclists, to went on board.

Godbye Genova.

In practice it is not so bad

After making some changes in the CAS algorithm and improving the prototype (basically, I write its core from scratch) I could study its behavior with larger collections. The results were positive because the growth of the shape pool is far below the simulated worst case. Indeed, after the third iteration the number of segments to add to shape pool decreases and within seventh iteration is very low. The chart bellow illustrates exactly this.

Shape pool growth (using a set of 273 models extracted from ESB)

CAS shape pool segment growth

As I was expecting, the context-aware segmentation (CAS) approach can potentially led to an exponential growth of the number of segments in the shape pool. Theoretically, if all the branches of the segmentation tree are expanded, after seven iterations the number of segments can grow so much that will be impossible to store in memory all their signatures. The charts below illustrate the worst case for two distinct collections with one and eight hundred models respectively.

Number of segments in shape pool

Memory necessary to store segment signatures