Authors:
Raul Beltrán B.
;
Julia Richter
and
Ulrich Heinkel
Affiliation:
Professorship Circuit and System Design, Chemnitz University of Technology, Reichenhainer Straße 70, 09126 Chemnitz, Germany
Keyword(s):
Climbing Motion Analysis, Movement Segmentation, Human Pose Estimation, Video Analysis.
Abstract:
The individual movement characterization of the human body parts is a fundamental task for the study of different activities executed by a person. Changes in position, speed and frequency of the different limbs reveal the kind of activity and allow us to estimate whether an action is well performed or not. Part of this characterization consists of establishing when the action begins and ends, but it is a difficult process when attempted by purely optical means since the subject’s pose in the image must first be extracted before proceeding with the movement variables identification. Human motion analysis has been approached in multiple studies through methods ranging from stochastic to artificial intelligence prediction, and more recently the latest research has been extended to the sport climbing employing the centre-of-mass analysis. In this paper, we present a method to identify the beginning and end of the movements of human body parts, through the analysis of kinematic variables
obtained from RGB-D videos, with the aim of motion analysis in climbing. Application tests with OpenPose, PoseNet and Vision are presented to determine the optimal framework for human pose estimation in this sports scenario, and finally, the proposed method is validated to segment the movements of a climber on the climbing wall.
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