Race Walking Computer Vision - Determining Legality of an Athlete

2027 · 2027 Competition

School: School of Computer and Information Sciences
Categories: Humanitarian, Data SciencePrimary

Project Overview

One Liner: Computer Vision Project that detects the legality of a race walking athlete.

Abstract

Computer Vision application that will detect and analyze the precise movement phases in Race Walking. With the help of AWS (SageMaker, S3, Lambda), OpenShot, and TensorFlow, our team is able to capture and label specific frames from video footage to train a model that will identify foot-ground contact points. These phases include heel strikes, full foot contact, toe contact, and toe-off, as well as scenarios when the foot is not touching the ground. The trained model will help identify the correct form and foot-ground contact in Race Walking, this will help athletes and coaches receive accurate feedback and analysis better.

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Team Members

Kush Patel
Kush Patel
Lead
Loren Lei
Dhruv Patel
Shivam Patel
Jeremy Torres

Advisors

Jeff Salvage
Jeff Salvage

Stakeholders

Jeff Salvage
Jeff Salvage