@article{(Open Science Index):https://publications.waset.org/pdf/7784, title = {Automated Service Scene Detection for Badminton Game Analysis Using CHLAC and MRA}, author = {Fumito Yoshikawa and Takumi Kobayashi and Kenji Watanabe and Nobuyuki Otsu}, country = {}, institution = {}, abstract = {Extracting in-play scenes in sport videos is essential for quantitative analysis and effective video browsing of the sport activities. Game analysis of badminton as of the other racket sports requires detecting the start and end of each rally period in an automated manner. This paper describes an automatic serve scene detection method employing cubic higher-order local auto-correlation (CHLAC) and multiple regression analysis (MRA). CHLAC can extract features of postures and motions of multiple persons without segmenting and tracking each person by virtue of shift-invariance and additivity, and necessitate no prior knowledge. Then, the specific scenes, such as serve, are detected by linear regression (MRA) from the CHLAC features. To demonstrate the effectiveness of our method, the experiment was conducted on video sequences of five badminton matches captured by a single ceiling camera. The averaged precision and recall rates for the serve scene detection were 95.1% and 96.3%, respectively.}, journal = {International Journal of Computer and Information Engineering}, volume = {4}, number = {2}, year = {2010}, pages = {331 - 334}, ee = {https://publications.waset.org/pdf/7784}, url = {https://publications.waset.org/vol/38}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 38, 2010}, }