This past week, we learnt about various tools for 3D modeling. We expanded our SketchUp toolkit, explored procedural modeling through CityEngine, and also used PhotoScan to build a 3D model of an artifact from some 2D pictures (Photogrammetry).
In terms of research questions for which 3D modeling and simulation would be appropriate methodology, what came to my mind first were modeling ancient artifacts and constructing small-scale 3D models of ancient architecture/landscape. In an art history class I took at Carleton, we looked at ancient Chinese bronze vessels. There are different kinds of them, each of different usage. Each kind, however, is of a very standard shape, and there are also several standard surface decoration patterns for these vessels (that indicate owners’ social classes).
With 3D modeling techniques, especially procedural modeling, we can easily construct 3D prototypes for different kinds of vessels, which might help us better classify them. Also, the 3D models of ancient artifacts and architecture/landscape can aid one to better understand how people lived hundreds or even thousands of years ago.
I found it hard to come up with an occasion when manual modeling would make the most sense. I guess sometimes when one tries to model an ancient artifact that is too delicate to be scanned or taken pictures of, we might need to resort to manual modeling. In most other occasions, scanning is likely to yield a more accurate model for small objects than manual modeling, and procedural modeling is likely to model large-scale objects much faster. Procedural modeling can potentially be combined with manual modeling to make the code-generated 3D models more accurate.
From reading Marie Saldana’s paper An Integrated Approach to the Procedural Modeling of Ancient Cities and Buildings, I got a sense that while procedural modeling allows rapid prototyping and interactive updating of 3D content, the process of finding the optimal set of “rules” is hard and requires some backward thinking. So I was wondering whether computer scientists can develop algorithms and programs that automatically generate the optimal set of “rules” when being fed with information about the objects to be modeled.