Abstract
Many methods such as biomechanics and coaching have been proposed to help people learn a certain movement. There have been proposals for methods to discover characteristics of movement based on information obtained from videos and sensors. Especially in sports, it is expected that these methods can provide hints to improve movement skills. However, conventional methods focus on individual movements, and do not consider cases where external factors influence the movement, such as combat sports. In this paper, we propose a novel method called the Extraction for Successful Movement method (XSM method). Applying the method, this paper focuses on throwing techniques in judo to discover key factors that induce successful throwing from the postures right before initiating the throwing techniques. We define candidate factors by observing the video scenes where the throwing techniques are successfully performed. The method demonstrates the significance of the key factors according to the predominance of factors by test and residual analysis. Applying the XSM method to the dataset obtained from the videos of the Judo World Championships, we demonstrate the validity of the method with discussing the key factors related to the successful throwing techniques.
Highlights
Sports are a fun activity which help us to maintain a healthy body
We have developed a system based on a statistical approach, called the Extraction for Successful Movements method (XSM method), that extracts the key factors by applying a dataset of available factors from body parts at a posture before a target movement
This paper proposed a novel method for finding the factors from postures before initiating a successful movement
Summary
Sports are a fun activity which help us to maintain a healthy body. When we want to be a good player in a sports activity, we put a lot of effort into acquiring key movements of specific motor skills. This paper proposes a novel method that derives key factors for effective learning of a movement in combat sports. It is necessary to develop a method that extracts the key factors of a target movement from videos based on an objective observation and provides feedback to the learners effectively. In [7], the authors propose a method that automatically determines skills of skiing and snowboarding by applying motion sensors in smartphone They focus on factors including tempo, symmetry, and dynamism that cause visual elegance of the movements. In order to eliminate the subjective opinions, there are attempts to quantify the skills from the model formulas using the coordinate values from video frames and the measured data from the sensor devices Those methods derive the key factors of the target movements by using mathematical and/or machine learning approaches. It is important to develop a novel method with an objective approach that derives the key factors of movements in combat sports
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
