Thesis Details
Running Motion Analysis
The goal of this thesis is to analyze body movement in running gait. The system works with recordings from two cameras, one from the side and one from the back. The problem is solved using a pose estimation algorithm based on the convolutional method. Multiple estimators are compared in this thesis. The final system uses the OpenPose framework and provides a library with calculations for many metrics used to evaluate the running gait. Results are then visualised in a multiplatform desktop application. Experiments were conducted on a private dataset of running recordings.
artificial intelligence, neural networks, computer vision, skeleton detection, pose estimation, running form, running, running gait, AI, movement detection, body position, camera, biomechanics, Python, kinematics, video
Bartík Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
Bařina David, Ing., Ph.D. (DCGM FIT BUT), člen
Kočí Radek, Ing., Ph.D. (DITS FIT BUT), člen
Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY FIT BUT), člen
@bachelorsthesis{FITBT23845,
author = "Radoslav Eli\'{a}\v{s}",
type = "Bachelor's thesis",
title = "Running Motion Analysis",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2021,
location = "Brno, CZ",
language = "english",
url = "https://www.fit.vut.cz/study/thesis/23845/"
}