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01.08.2013 | Industrial and Commercial Application

A methodology for detection and estimation in the analysis of golf putting

verfasst von: Micael S. Couceiro, David Portugal, Nuno Gonçalves, Rui Rocha, J. Miguel A. Luz, Carlos M. Figueiredo, Gonçalo Dias

Erschienen in: Pattern Analysis and Applications | Ausgabe 3/2013

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Abstract

This paper presents a methodology for visual detection and parameter estimation to analyze the effects of the variability in the performance of golf putting. A digital camera was used in each trial to track the putt gesture. The detection of the horizontal position of the golf club was performed using a computer vision technique, followed by an estimation algorithm divided in two different stages. On a first stage, diverse nonlinear estimation techniques were used and evaluated to extract a sinusoidal model of each trial. Secondly, several expert golf player trials were analyzed and, based on the results of the first stage, the Darwinian particle swarm optimization (DPSO) technique was employed to obtain a complete kinematical analysis and a characterization of each player’s putting technique. In this work, it is intended not only to test the performance of the DPSO method, but also to present a novel study in this field by identifying a putting “signature” of each player.

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Titel: A methodology for detection and estimation in the analysis of golf putting
verfasst von: Micael S. Couceiro
David Portugal
Nuno Gonçalves
Rui Rocha
J. Miguel A. Luz
Carlos M. Figueiredo
Gonçalo Dias
Publikationsdatum: 01.08.2013
Verlag: Springer London
Erschienen in: Pattern Analysis and Applications / Ausgabe 3/2013
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI: https://doi.org/10.1007/s10044-012-0276-8

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