Stanford researchers have created a single diffusion generative model, DiffusionPoser, that can reconstruct human motion in real-time from arbitrary body sensor configurations, with broad application in a variety of motion capture end uses.
Active manipulation of light beams is required for a range of emerging optical technologies, including sensing, optical computing, virtual/augmented reality, dynamic holography, and computational imaging.
A Stanford bioengineering researcher developed an optical sensor based muscle and body motion tracking system for use with prosthetics and wearable human machine interfaces.
Stanford researchers have patented an automated method for generating articulated human models consisting of both morphological and kinematic model data.
Stanford researchers have patented a data-driven method for building a human shape model that spans variation in both subject shape and pose. The method is based on a representation that incorporates both articulated and non-rigid deformations.
Researchers from Stanford University and the Max Planck Institute have patented a new marker-less approach to capturing human performances from multi-view video.