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.
Although tracking has been studied for decades, real-time tracking algorithms often suffer from low accuracy and poor robustness when confronted with difficult, real-world data.
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.
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.