Stereo camera systems have been used to track markers attached to a racket, allowing its position to be obtained in three-dimensional (3D) space. Typically, markers are manually selected on the image plane, but this can be time-consuming. A markerless system based on one stationary camera estimating 3D racket position data is desirable for research and play. The markerless method presented in this paper relies on a set of racket silhouette views in a common reference frame captured with a calibrated camera and a silhouette of a racket captured with a camera whose relative pose is outside the common reference frame. The aim of this paper is to provide validation of these single view fitting techniques to estimate the pose of a tennis racket. This includes the development of a calibration method to provide the relative pose of a stationary camera with respect to a racket. Mean static racket position was reconstructed to within ±2 mm. Computer generated camera poses and silhouette views of a full size racket model were used to demonstrate the potential of the method to estimate 3D racket position during a simplified serve scenario. From a camera distance of 14 m, 3D racket position was estimated providing a spatial accuracy of 1.9 ± 0.14 mm, similar to recent 3D video marker tracking studies of tennis.
Tennis racket manufacturers rely on subjective assessments from testers during the development process. However, these assessments often lack validity and include multiple sources of inconsistency in the way testers make subjective ratings. The purpose of this research was to investigate the suitability of the free-choice profiling (FCP) method in combination with principle component analysis (PCA) and multiple factor analysis (MFA) to determine the sensory profile of rackets. FCP was found to be a suitable technique to quickly evaluate the sensory profile of rackets; however, consumer testers tended to use ill-defined, industry-generated terms, which negatively impacted discrimination and inter-rater agreement. Discrimination and inter-rater agreement improved for attributes referring to measurable parameters of the rackets, such as vibration. This study furthers our understanding of tennis racket feel and supports racket engineers in designing new subjective testing methods, which provide more meaningful data regarding racket feel.
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