Computer Vision Body Posture Quantification for Table Tennis Loop Drive
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Solution Overview
Problem
Current technologies lack comprehensive and accurate methods to quantify and capture the specific body postures essential for effective loop drive techniques in table tennis, which are crucial for improving training quality and player performance.
Innovation Solution
A computer vision-based system that processes video recordings of table tennis players to segment and quantify body postures before and during the loop drive technique, using image processing and pattern recognition techniques to isolate and measure key angles and movements, such as waist rotation, arm positions, and racket displacement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computer vision techniques are applied to capture body postures in table tennis, then measurement precision of body postures is improved, but device complexity increases
Solution Approach 1:
The patent applies multi-functionality by using a single video recording device to capture multiple aspects of table tennis technique simultaneously - body postures, racket positions, ball trajectories, and player movements all from one video source, eliminating the need for multiple specialized sensors or measurement devices
Solution Approach 2:
The patent replaces complex mechanical measurement systems (such as motion capture cameras, sensors, and tracking devices) with computer vision technology that processes standard video recordings through image processing and pattern recognition algorithms to extract posture data
2Measurement precision
If video recordings are segmented into multiple parts, then measurement precision of specific motions is improved, but loss of time increases
Solution Approach 1:
The patent divides the table tennis stroke into distinct phases (preparation, contact, follow-through) and segments the video recording accordingly, allowing focused analysis of each motion phase with specific posture parameters extracted from relevant time segments only
Solution Approach 2:
The patent performs preliminary actions by automatically detecting key events (ball contact, racket position) in the video and pre-segmenting the footage into meaningful phases before detailed posture analysis, so that subsequent processing focuses only on relevant time segments
Data Source
AI summary
Disclosed are techniques for quantifying body postures of a player employing a loop drive technique to strike a ball, such as performed in table tennis activities. A video recording of a player striking a ball with a loop drive technique is received and divided, using image processing techniques, into two segments: the first concerning player body postures before the ball is hit, and the second concerning body postures from the moment of impact between the ball and racket and the subsequent follow-through body postures. Then, image processing techniques are again leveraged to isolate and quantify specific body postures contributing to a loop drive technique in a given segment.