Beach volleyball serve type recognition
© 2016 ACM. We present results on beach volleyball serve recognition and classification from a wrist-worn gyroscope deployed with semi-professional beach volleyball players. We trained a template-based recognition system based on a Warping Longest Common Subsequence algorithm to spot serves, and pot...
Saved in:
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Conference or Workshop Item |
| Published: |
2018
|
| Subjects: | |
| Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/43447 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Mahidol University |
| id |
th-mahidol.43447 |
|---|---|
| record_format |
dspace |
| spelling |
th-mahidol.434472019-03-14T15:04:30Z Beach volleyball serve type recognition L. Ponce Cuspinera Sakura Uetsuji F. J.Ordonez Morales Daniel Roggen University of Sussex Mahidol University Computer Science © 2016 ACM. We present results on beach volleyball serve recognition and classification from a wrist-worn gyroscope deployed with semi-professional beach volleyball players. We trained a template-based recognition system based on a Warping Longest Common Subsequence algorithm to spot serves, and potentially distinguish among 4 common serve types. This shows the potential of wearable technologies in beach volleyball, which could offer precise sport analytics. 2018-12-11T02:37:36Z 2019-03-14T08:04:30Z 2018-12-11T02:37:36Z 2019-03-14T08:04:30Z 2016-09-12 Conference Paper International Symposium on Wearable Computers, Digest of Papers. Vol.12-16-September-2016, (2016), 44-45 10.1145/2971763.2971781 2-s2.0-84989295869 https://repository.li.mahidol.ac.th/handle/123456789/43447 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84989295869&origin=inward |
| institution |
Mahidol University |
| building |
Mahidol University Library |
| continent |
Asia |
| country |
Thailand Thailand |
| content_provider |
Mahidol University Library |
| collection |
Mahidol University Institutional Repository |
| topic |
Computer Science |
| spellingShingle |
Computer Science L. Ponce Cuspinera Sakura Uetsuji F. J.Ordonez Morales Daniel Roggen Beach volleyball serve type recognition |
| description |
© 2016 ACM. We present results on beach volleyball serve recognition and classification from a wrist-worn gyroscope deployed with semi-professional beach volleyball players. We trained a template-based recognition system based on a Warping Longest Common Subsequence algorithm to spot serves, and potentially distinguish among 4 common serve types. This shows the potential of wearable technologies in beach volleyball, which could offer precise sport analytics. |
| author2 |
University of Sussex |
| author_facet |
University of Sussex L. Ponce Cuspinera Sakura Uetsuji F. J.Ordonez Morales Daniel Roggen |
| format |
Conference or Workshop Item |
| author |
L. Ponce Cuspinera Sakura Uetsuji F. J.Ordonez Morales Daniel Roggen |
| author_sort |
L. Ponce Cuspinera |
| title |
Beach volleyball serve type recognition |
| title_short |
Beach volleyball serve type recognition |
| title_full |
Beach volleyball serve type recognition |
| title_fullStr |
Beach volleyball serve type recognition |
| title_full_unstemmed |
Beach volleyball serve type recognition |
| title_sort |
beach volleyball serve type recognition |
| publishDate |
2018 |
| url |
https://repository.li.mahidol.ac.th/handle/123456789/43447 |
| _version_ |
1763487374326628352 |