Researchers in the Murmann Mixed Signal Group have developed a pipelined chip architecture with inverted residual and linear bottlenecks-based networks for energy efficient Machine Learning inference on edge devices.
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 developed a method called KleinPAT, for creating sound models in seconds, making it cost effective to simulate sounds for many different objects in a virtual environment.
Stanford inventors have developed a new approach to tackling the vergence-accommodation conflict, which is a common contributor to discomfort associated with virtual reality setups.
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.
Stanford researchers have patented the "Wolverine," a mobile, wearable haptic device designed for simulating the grasping of rigid objects in virtual reality.
A team of researchers from the Stanford Artificial Intelligence Laboratory have patented a portfolio of innovations that harness depth sensing technology to analyze human motion for touch-free control of devices and motion capture.
A team of researchers from the Stanford Artificial Intelligence Laboratory have developed a portfolio of patented innovations that harness depth sensing technology to analyze human motion for touch-free control of devices and motion capture.
Researchers from Stanford University and the Max Planck Institute have patented a new marker-less approach to capturing human performances from multi-view video.
A team of researchers from the Stanford Artificial Intelligence Laboratory have developed a portfolio of patented innovations that harness depth sensing technology to analyze human motion for touch-free control of devices and motion capture.