Extracting Player’s Stance Information from 3D Motion Data: A Case Study in Tennis Groundstrokes

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• 关键词：Exergames ; Sport and rehabilitation ; Biomechanics ; Augmented coaching systems (ACS) ; Human motion modelling and analysis (HMMA)
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9555
• 期：1
• 页码：307-318
• 全文大小：1,582 KB
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• 作者单位：Boris Bačić (15)
  
  15. School of Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand
  
• 丛书名：Image and Video Technology ᾿PSIVT 2015 Workshops
• ISBN：978-3-319-30285-0
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

This study presents a novel approach towards computing elements of balance, movement fluidity and reaction time, the foundations of which are commonly introduced in tennis as swing stance. The achieved results utilising presented algorithms, show 100 % recognition of tennis swings (forehands and backhands) and swing stance angle extractions from the 3D test data set. The data set was captured at 50 Hz without ball impact information using a stationary multi-camera setup. The next generation of exergames and augmented coaching technologies, utilising the presented approach for processing players’ footwork and stance will enable research advancements in human performance and further developments towards improving proprioception and kinaesthetic awareness. Determining body orientation within a temporal and spatial activity pattern to predict the follow-up action(s) may also enable advancements such as improving safety in surveillance, robot and automotive vision.