Webinar (Tutorial): Quantitative Movement Analysis Using Single-camera Videos, Part 2 of 2

Lukasz Kidzinski of Stanford University presents a short hands-on tutorial aimed at getting individuals started on running deep learning algorithms in the cloud to analyze movement from a single-camera video. He demonstrates the OpenPose pose estimation software; highlights and discusses common preprocessing issues, such as missing data, noise, and bias; and discusses techniques to resolve such issues. He also guides attendees in using the pre-processed data to derive estimates of metrics used in research and clinical applications.

This webinar is offered jointly with the Restore Center (https://restore.stanford.edu/), an NIH-funded Medical Rehabilitation Research Resource Network Center at Stanford University.

Watch part 1 of this webinar - a presentation on the research on quantitative movement analysis using single-camera videos in children with cerebral palsy: Webinar: Quantitative Movement Analys...
Explore the tutorial: https://github.com/stanfordnmbl/mobil...
Browse through Q&A: https://mobilize.stanford.edu/wp-cont...