weSport: Utilising Wrist-Band Sensing to Detect Player Activities in Basketball Games

Bai, Lu and Efstratiou, Christos and Ang, Chee Siang (2016) weSport: Utilising Wrist-Band Sensing to Detect Player Activities in Basketball Games. In: WristSense 2016: Workshop on Sensing Systems and Applications Using Wrist Worn Smart Devices (co-located with IEEE PerCom 2016), March 14, 2016, Sydney, Australia. (Full text available)

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Abstract

Wristbands have been traditionally designed to track the activities of a single person. However there is an opportunity to utilize the sensing capabilities of wristbands to offer activity tracking services within the domain of team-based sports games. In this paper we demonstrate the design of an activity tracking system capable of detecting the players’ activities within a one-to-one basketball game. Relying on the inertial sensors of wristbands and smartphones, the system can capture the shooting attempts of each player and provide statistics about their performance. The system is based on a two- level classification architecture, combining data from both players in the game. We employ a technique for semi-automatic labelling of the ground truth that requires minimum manual input during a training game. Using a single game as a training dataset, and applying the classifier on future games we demonstrate that the system can achieve a good level of accuracy detecting the shooting attempts of both players in the game (precision 91.34%, recall 94.31%).

Item Type: Conference or workshop item (Paper)
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76 Computer software
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Depositing User: Christos Efstratiou
Date Deposited: 23 Mar 2016 14:25 UTC
Last Modified: 19 Apr 2016 08:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/54612 (The current URI for this page, for reference purposes)
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