Paper Info
Title
Beach volleyball serve type recognition.
Abstract
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.
Year
DOI
Venue
2016
10.1145/2971763.2971781
ISWC
Keywords
Field
DocType
Wearable, Beach volleyball, WLCSS, sports, recognition
Computer vision,Gyroscope,Image warping,Longest common subsequence problem,Recognition system,Computer science,Wearable computer,Artificial intelligence,Analytics,Wearable technology
Conference
ISSN
Citations 
PageRank 
1550-4816
1
0.35
References 
Authors
3
4
Name
Order
Citations
PageRank
Luis Ponce Cuspinera171.39
Sakura Uetsuji210.35
Francisco Javier Ordóñez Morales3493.34
Daniel Roggen41851137.05