Blog #1: Solving the Fashion Fit Crisis with Open Source Tech

For my field study, I am trying to  develop a digital virtual fitting room to address the "trillion-dollar problem" of online returns, which can soar to 40% because of poor garment fit. While I initially considered using a proprietary Engine bu then  I have pivoted to a more specialized, open-source pipeline that prioritizes anatomy accuracy and real  time physics with less programming and extensive customization.

One of the key findings of my research is that many professional fitting tools tend to produce avatars that are “too smooth” or perfectly symmetrical. Such models do not take into account the realities of age, including the distribution of body fat, contours of muscle, sagging and asymmetry. To fill this gap, I am using MakeHuman for parametric modeling and MeshLab to clean and process 3D point clouds to create a more realistic human form.

I rigged the characters with mixamo, and simulated the cloth using an Enhanced PBD framework. The cloth simulation is believable, and optimized to be used in normal devices. This student-friendly approach aims for hyper-personalized sizing with an error rate of less than 1%, dramatically improving consumer experience and cutting down on industry waste.