Formulating the 3D modeling problem
“All models are wrong, but some are useful” is a popular aphorism in statistics. It suggests that it is often hard to mathematically model all the tiny details of a problem. A model will always be an approximation of reality, but some models are more accurate and, therefore, more useful than others.
In the field of machine learning, modeling a problem generally involves the following two components:
- Mathematically formulating the problem
- Building algorithms to solve that problem under the constraints and boundaries of that formulation
Good algorithms used on badly formulated problems often result in sub-optimal models. However, less powerful algorithms applied to a well-formulated model can sometimes result in great solutions. This insight is especially true for building 3D human body models.
The goal of this modeling problem is to create realistic animated human bodies. More importantly, this should represent...
