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Table tennis and computer vision: a monocular event classifier
© Springer International Publishing Switzerland 2016. Detecting events in table tennis using monocular video sequences for match-play officiating is challenging. Here a low-cost monocular video installation generates image sequences and, using the Horn-Schunck Optical Flow algorithm, ball detection...
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| Main Authors: | , , , |
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| Format: | Default Conference proceeding |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://hdl.handle.net/2134/20220 |
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| _version_ | 1818172352546996224 |
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| author | Kevin M. Oldham Paul Chung Eran Edirisinghe Ben Halkon |
| author_facet | Kevin M. Oldham Paul Chung Eran Edirisinghe Ben Halkon |
| author_sort | Kevin M. Oldham (7167899) |
| collection | Figshare |
| description | © Springer International Publishing Switzerland 2016. Detecting events in table tennis using monocular video sequences for match-play officiating is challenging. Here a low-cost monocular video installation generates image sequences and, using the Horn-Schunck Optical Flow algorithm, ball detection and location processing captures sudden changes in the ball’s motion. It is demonstrated that each abrupt change corresponds to a distinct event pattern described by its combined velocity, acceleration and bearing. Component motion threshold values are determined from the analysis of a range of table tennis event video sequences. The novel event classifier reviews change in motion data against these thresholds, for use in a rules based officiating decision support system. Experimental results using this method demonstrate an event classification success rate of 95.9%. |
| format | Default Conference proceeding |
| id | rr-article-9401099 |
| institution | Loughborough University |
| publishDate | 2016 |
| record_format | Figshare |
| spelling | rr-article-94010992016-01-01T00:00:00Z Table tennis and computer vision: a monocular event classifier Kevin M. Oldham (7167899) Paul Chung (1250973) Eran Edirisinghe (1257828) Ben Halkon (1256355) Other information and computing sciences not elsewhere classified Event classification Table tennis Ball Segmentation Detection Computer vision Optical flow Information and Computing Sciences not elsewhere classified © Springer International Publishing Switzerland 2016. Detecting events in table tennis using monocular video sequences for match-play officiating is challenging. Here a low-cost monocular video installation generates image sequences and, using the Horn-Schunck Optical Flow algorithm, ball detection and location processing captures sudden changes in the ball’s motion. It is demonstrated that each abrupt change corresponds to a distinct event pattern described by its combined velocity, acceleration and bearing. Component motion threshold values are determined from the analysis of a range of table tennis event video sequences. The novel event classifier reviews change in motion data against these thresholds, for use in a rules based officiating decision support system. Experimental results using this method demonstrate an event classification success rate of 95.9%. 2016-01-01T00:00:00Z Text Conference contribution 2134/20220 https://figshare.com/articles/conference_contribution/Table_tennis_and_computer_vision_a_monocular_event_classifier/9401099 CC BY-NC-ND 4.0 |
| spellingShingle | Other information and computing sciences not elsewhere classified Event classification Table tennis Ball Segmentation Detection Computer vision Optical flow Information and Computing Sciences not elsewhere classified Kevin M. Oldham Paul Chung Eran Edirisinghe Ben Halkon Table tennis and computer vision: a monocular event classifier |
| title | Table tennis and computer vision: a monocular event classifier |
| title_full | Table tennis and computer vision: a monocular event classifier |
| title_fullStr | Table tennis and computer vision: a monocular event classifier |
| title_full_unstemmed | Table tennis and computer vision: a monocular event classifier |
| title_short | Table tennis and computer vision: a monocular event classifier |
| title_sort | table tennis and computer vision: a monocular event classifier |
| topic | Other information and computing sciences not elsewhere classified Event classification Table tennis Ball Segmentation Detection Computer vision Optical flow Information and Computing Sciences not elsewhere classified |
| url | https://hdl.handle.net/2134/20220 |