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  1. National Taiwan Ocean University Research Hub
  2. 工學院
  3. 機械與機電工程學系
請用此 Handle URI 來引用此文件: http://scholars.ntou.edu.tw/handle/123456789/21995
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dc.contributor.authorWen, Bor-Jiunnen_US
dc.contributor.authorChang, Che-Ruien_US
dc.contributor.authorLan, Chun-Weien_US
dc.contributor.authorZheng, Yi-Chenen_US
dc.date.accessioned2022-07-01T01:53:02Z-
dc.date.available2022-07-01T01:53:02Z-
dc.date.issued2022-06-01-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/21995-
dc.description.abstractThis study analyzed the characteristics of pitched baseballs from TV broadcast videos to understand the effects of the Magnus force on a pitched-baseball trajectory using aerodynamic theory. Furthermore, an automatic measurement and analysis system for pitched-baseball trajectories, ball speeds, and spin rates was established, capturing the trajectory of the baseball thrown by the pitcher before the catcher catches it and analyzing its related dynamic parameters. The system consists of two parts: (1) capturing and detecting the pitched baseball in all frames of the video using the YOLOv3-tiny deep learning algorithm and automatically recording the coordinates of each detected baseball position; (2) automatically calculating the average speed and spin rate of the pitched baseball using aerodynamic theory. As the baseball thrown by the pitcher is fast, and live-action TV videos like sports and concerts are typically at least 24 fps or more, this study used YOLOv3-tiny algorithm to speed up the calculation. Finally, the system automatically presented pitching data on the screen, and the pitching information in the baseball game was easily obtained and recorded for further discussion. The system was tested using 30 videos of pitched baseballs and could effectively capture the baseball trajectories, throw points, catch points, and vertical displacements. Compared with the values from the TV broadcast, the average errors on the calculated ball speed and spin rate were 1.88% and 7.51%, respectively. Using the ratio of the spin rate and ball speed as a parameter to analyze the pitching state of the pitcher's four-seam fastball in the Nippon Professional Baseball and Major League Baseball matches, it was observed that when this ratio increased, the Magnus displacement of the ball increased, thereby decreasing its late break. Therefore, the developed system provides scientific pitching data to improve the performance of baseball pitchers.en_US
dc.language.isoEnglishen_US
dc.publisherMDPIen_US
dc.relation.ispartofAPPLIED SCIENCES-BASELen_US
dc.subjectmagnus forceen_US
dc.subjectpitched-baseball trajectoryen_US
dc.subjectYOLOv3-tiny deep learning algorithmen_US
dc.subjectball speeden_US
dc.subjectspin rateen_US
dc.titleMagnus-Forces Analysis of Pitched-Baseball Trajectories Using YOLOv3-Tiny Deep Learning Algorithmen_US
dc.typejournal articleen_US
dc.identifier.doi10.3390/app12115540-
dc.identifier.isiWOS:000808988800001-
dc.relation.journalvolume12en_US
dc.relation.journalissue11en_US
dc.identifier.eissn2076-3417-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.languageiso639-1English-
item.fulltextno fulltext-
item.grantfulltextnone-
item.openairetypejournal article-
crisitem.author.deptCollege of Engineering-
crisitem.author.deptDepartment of Mechanical and Mechatronic Engineering-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.orcid0000-0003-0163-6070-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCollege of Engineering-
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