From Image to Stability: Learning Dynamics from Human Pose

no code implementations • ECCV 2020 • Jesse Scott, Bharadwaj Ravichandran, Christopher Funk, Robert T. Collins, Yanxi Liu

We propose and validate two end-to-end deep learning architectures to learn foot pressure distribution maps (dynamics) from 2D or 3D human pose (kinematics).

From Kinematics To Dynamics: Estimating Center of Pressure and Base of Support from Video Frames of Human Motion

no code implementations • 2 Jan 2020 • Jesse Scott, Christopher Funk, Bharadwaj Ravichandran, John H. Challis, Robert T. Collins, Yanxi Liu

To gain an understanding of the relation between a given human pose image and the corresponding physical foot pressure of the human subject, we propose and validate two end-to-end deep learning architectures, PressNet and PressNet-Simple, to regress foot pressure heatmaps (dynamics) from 2D human pose (kinematics) derived from a video frame.

Learning Dynamics from Kinematics: Estimating 2D Foot Pressure Maps from Video Frames

no code implementations • 30 Nov 2018 • Christopher Funk, Savinay Nagendra, Jesse Scott, Bharadwaj Ravichandran, John H. Challis, Robert T. Collins, Yanxi Liu

In biomechanics, Center of Pressure (CoP) is used in studies of human postural control and gait.