A lot of research has recently focused on the problem of capturing the geometry and motion of garments. Such work usually relies on special markers printed on the fabric to establish temporally coherent correspondences between points on the garment's surface at different times. Unfortunately, this approach is tedious and prevents the capture of off-the-shelf clothing made from interesting fabrics.

In this talk I will summarize recent advances in detailed, marker-free garment capture resulting from our research at the University of British Columbia. I will first discuss our physical acquisition setup, including camera synchronization and rolling shutter compensation using stroboscopic illumination. I will then describe our garment capture approach, where we establish temporally coherent parameterizations between incomplete geometries that we extract at each timestep with a multiview stereo algorithm. Finally, I will discuss a method for reintroducing fine folds into the captured models using data-driven dynamic wrinkling. As a result of this work, we are able to capture the geometry and motion of unpatterned, off-the-shelf garments made from a range of different fabrics, with realistic dynamic folds.