Badminton Stroke Classification Jia-Wei Chang advised by Prof. Chih-Wei Yi Department of Computer Science National Chiao Tung University 研究題目: 智慧球拍應用於羽球球種分類 影片: 簡單介紹我的研究，結束後會再作進一步解說

Abstract In this talk, a badminton stroke classification system utilizing wearable devices, mobile platforms, and machine learning techniques will be introduced. The system has two key modules, stroke detection and stroke classification. In the stroke detection module, an algorithm was proposed to detect stroke events and their happening times based on voiceprint features. The accuracy of event detection is 100% in our experiments. To have better classification performance, four classifiers, including the random forest, SMO with Polynomial Kernel, SMO with RBF Kernel, and Naïve Bayes, were evaluated to classify six stroke types based on IMU data. Our results showed that SMO with Polynomial Kernel reaches an average accuracy rate 96.83% and outperforms the other three classifiers.

Short Bio Dr. Chih-Wei Yi received his Ph.D. degree in Computer Science from the Illinois Institute of Technology in 2005, and B.S. degree in Mathematics and M.S. degrees in Computer Science and Information Engineering from the National Taiwan University in 1991 and 1993, respectively. He is currently a Professor with the Department of Computer Science and the Director of the Institute of Network Engineering, National Chiao Tung University. He is a member of the IEEE. He had been a Senior Research Fellow of the Department of Computer Science, City University of Hong Kong. He was bestowed the Outstanding Young Engineer Award by the Chinese Institute of Engineers in 2009, and the Young Scholar Best Paper Award by IEEE IT/COMSOC Taipei/Tainan Chapter in 2010. He received the Best Paper Award at ITST 2012. He received the 3-year Outstanding Young Researcher Grant from the National Science Council, Taiwan in 2012. His research focuses on wireless ad hoc and sensor networks, intelligent transportation systems, mobile sensing, and data mining.