Search Results for author: Jesse Scott

Found 4 papers, 0 papers with code

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).

Image-based Stability Quantification

no code implementations23 Jun 2022 Jesse Scott, John Challis, Robert T. Collins, Yanxi Liu

Quantitative evaluation of human stability using foot pressure/force measurement hardware and motion capture (mocap) technology is expensive, time consuming, and restricted to the laboratory.

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

no code implementations2 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.

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