EAI Endorsed Transactions on Creative Technologies 15(5): e2

Research Article

Using Video Analysis and Machine Learning for Predicting Shot Success in Table Tennis

Download57 downloads
  • @ARTICLE{10.4108/eai.20-10-2015.150096,
        author={Lukas Draschkowitz and Christoph Draschkowitz and Helmut Hlavacs},
        title={Using Video Analysis and Machine Learning for Predicting Shot Success in Table Tennis},
        journal={EAI Endorsed Transactions on Creative Technologies},
        volume={15},
        number={5},
        publisher={EAI},
        journal_a={CT},
        year={2015},
        month={10},
        keywords={machine learning, sports video analysis, ball tracking, video processing, video information retrieval, video mining, multimedia data mining},
        doi={10.4108/eai.20-10-2015.150096}
    }
    
  • Lukas Draschkowitz
    Christoph Draschkowitz
    Helmut Hlavacs
    Year: 2015
    Using Video Analysis and Machine Learning for Predicting Shot Success in Table Tennis
    CT
    EAI
    DOI: 10.4108/eai.20-10-2015.150096
Lukas Draschkowitz1,*, Christoph Draschkowitz1, Helmut Hlavacs1
  • 1: University of Vienna, Faculty of Computer Science, Research Group Entertainment Computing
*Contact email: lukas.draschkowitz@chello.at

Abstract

Coaching professional ball players has become more and more dicult and requires among other abilities also good tactical knowledge. This paper describes a program that can assist in tactical coaching for table tennis by extracting and analyzing video data of a table tennis game. The here described application automatically extracts essential information from a table tennis match, such as speed, length, height and others, by analyzing a video of that game. It then uses the well known machine learning library " to learn about the success of a shot. Generalization is tested by using a training and a test set. The program then is able to predict the outcome of shots with high accuracy. This makes it possible to develop and verify tactical suggestions for players as part of an automatic analyzing and coaching tool, completely independent of human interaction.