@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%,
	    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},