Interactive exploration of drapes by simulation parameters

How similar a virtual product is to a real product is one of the most important issues when using virtual simulation to develop real apparel designs. The first step to achieve high similarity is finding optimal simulation parameters for the desired fabrics. However, it is notoriously difficult to find an optimal parameter set that reproduces the physical properties of a specific fabric as closely as possible. It is because the relationship between the changes of simulation parameters and drape shapes is highly non-linear, not intuitive, and hard to be predicted even by experts. Therefore, users have to repeat trial and error based on personal experience until they find satisfactory results, which is time consuming due to the simulation time required for each trial. To handle this problem, we proposed a neural network model that learns the relationship between the parameter space and the drape space, then we presented a user interface that allows users to quickly explore the extensive drape space through simulation parameters. To validate our method, we provided our UI with experts in the fashion design industry and conducted user studies with them for qualitative evaluation.