Using Wrist-Worn Activity Recognition for Basketball Game Analysis

被引:21
作者
Hoelzemann, Alexander [1 ]
Van Laerhoven, Kristof [1 ]
机构
[1] Univ Siegen, Siegen, North Rhine Wes, Germany
来源
5TH INTERNATIONAL WORKSHOP ON SENSOR-BASED ACTIVITY RECOGNITION AND INTERACTION (IWOAR 2018) | 2018年
关键词
activity recognition; wearable sports analysis; wrist-worn IMU sensors; basketball action detection;
D O I
10.1145/3266157.3266217
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Game play in the sport of basketball tends to combine highly dynamic phases in which the teams strategically move across the field, with specific actions made by individual players. Analysis of basketball games usually focuses on the locations of players at particular points in the game, whereas the capture of what actions the players were performing remains underrepresented. In this paper, we present an approach that allows to monitor players' actions during a game, such as dribbling, shooting, blocking, or passing, with wrist-worn inertial sensors. In a feasibility study, inertial data from a sensor worn on the wrist were recorded during training and game sessions from three players. We illustrate that common features and classifiers are able to recognize short actions, with overall accuracy performances around 83.6% (k-Nearest-Neighbor) and 87.5% (Random Forest). Some actions, such as jump shots, performed well (+/- 95% accuracy), whereas some types of dribbling achieving low (+/- 44%) recall.
引用
收藏
页数:6
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