Racewalking Gait Analysis Based on RGB Images

Abstract

In this paper, we propose a novel method for race-walking gait analysis based on RGB images. Our method provides an efficient way to quantitatively evaluate an athlete's racewalking techniques, which enables them to improve through more precise training programs accordingly. Our method includes angle prediction and pace measurement, which in combination can indicates the impact of a racewalker's unique racewalking gait on his/her competition performance in terms of time. 1) In angle prediction, the calculation about the angle of limbs is based on the coordinates of the human skeleton points. 2) In pace measurement, we derive the racewalker's pace by detecting the distance covered by the racewalker in RGB images during a period of time. Finally, the results of a practical experiment on professional racewalking athletes show that our method can efficiently quantify and analyze the racewalking gait with high precision.