JOURNAL ARTICLE

Markerless Tracking of Tennis Racket Motion Using a Camera

Nathan ElliottSimon ChoppinSimon GoodwillTom Allen

Year: 2014 Journal:   Procedia Engineering Vol: 72 Pages: 344-349   Publisher: Elsevier BV

Abstract

This research is concerned with tracking tennis racket movements. Previously, stereo camera systems have been used to track markers attached to rackets, which allows for racket movements to be obtained in three-dimensions. Typically, markers are manually selected on the image plane but this can be time consuming and inaccurate. This paper discusses a markerless method to measure three-dimensional racket movements using a camera. The method relies on a silhouette of a racket captured with a camera whose relative pose (rotation and translation) is unknown. A candidate relative pose is used to measure the inconsistency between the silhouette and a set of racket silhouettes captured with a fully calibrated camera. The measure of inconsistency can be formulated as a cost function associated with the candidate relative pose. By adjusting parameters of the pose to minimise the cost, an accurate estimation for the true pose of the racket can be made. A validation scheme was developed to compare pose estimates with data obtained using camera calibration software. Rotation about the axis of x, y, z' were accurate to within 2.5° for 88, 90 and 86 % of estimates respectively and resultant translation to within 5 mm for 72% of estimates. This research is the first step in a process to fully validate a novel method for measuring tennis racket movements in real play conditions.

Keywords:
Racket Computer vision Silhouette Artificial intelligence Rotation (mathematics) Computer science Measure (data warehouse) Translation (biology) Pose Camera resectioning Motion analysis Engineering Swing

Metrics

18
Cited By
1.93
FWCI (Field Weighted Citation Impact)
16
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Optical measurement and interference techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Measurement and Metrology Techniques
Physical Sciences →  Engineering →  Mechanical Engineering

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