Title: On Building Digital Humans
Speaker: Michael Black
Abstract: The human body is complex and deformable. For many applications in computer vision, graphics, fashion, and medicine, having a realistic, low-dimensional, 3D model of the body is useful. Getting a good one, however, is difficult. This talk will review the history of our work on learning 3D models of the human body from 3D scans. It will try to answer “what” is a body model, “why” it is useful, and “how” to build one. It will summarize how to accurately align 3D meshes of bodies in arbitrary poses, how to build a statistical model of body shape and non-rigid pose variation, and how to fit such models to data including 3D scans, Kinect data, or mocap markers. The talk will also describe recent work on capturing and modeling the dynamics of soft tissue motion using our one-of-a-kind 4D body scanner.
Bio: Michael Black received his B.Sc. from the University of British Columbia (1985), his M.S. from Stanford (1989), and his Ph.D. from Yale University (1992). After post-doctoral research at the University of Toronto, he worked at Xerox PARC as a member of research staff and an area manager. From 2000 to 2010 he was on the faculty of Brown University in the Department of Computer Science (Assoc. Prof. 2000-2004, Prof. 2004-2010). He is one of the founding directors at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department. He is an Honorarprofessor at the University of Tuebingen, Visiting Professor at ETH Zürich, and Adjunct Professor (Research) at Brown University. His work has won several awards including the IEEE Computer Society Outstanding Paper Award (1991), Honorable Mention for the Marr Prize (1999 and 2005), the 2010 Koenderink Prize for Fundamental Contributions in Computer Vision, and the 2013 Helmholtz Prize for work that has stood the test of time. He is a foreign member of the Royal Swedish Academy of Sciences. He is also a co-founder and board member of Body Labs Inc.
Background Material:
Shape and from Kinect (ICCV’15)
SMPL body model (SIGGRAPH Asia ’15)
Dyna (SIGGRAPH ’15)
MoSh (SIGGRAPH Asia ’14)
FAUST (CVPR’14)
Sponsored by the Stanford Computer Forum