摘要
Sports big data technology has become an important technological means of modern sports competition. This paper realizes a novel soccer video event detection algorithm based on self-attention. It extracts key frames through self-attention mechanism, and then obtains the characteristics of time window level through NetVLAD network. Finally, each video clip is classified into 4 types of events (goals, red/yellow card, substitutions and others). The experimental results show that with the introduction of the self-attention mechanism, the classification accuracy on the SoccerNet data set has improved from 67.2% to 74.3%.
源语言 | 英语 |
---|---|
主期刊名 | 2020 IEEE 6th International Conference on Computer and Communications, ICCC 2020 |
出版商 | Institute of Electrical and Electronics Engineers Inc. |
页 | 1852-1856 |
页数 | 5 |
ISBN(电子版) | 9781728186351 |
DOI | |
出版状态 | 已出版 - 11 12月 2020 |
活动 | 6th IEEE International Conference on Computer and Communications, ICCC 2020 - Chengdu, 中国 期限: 11 12月 2020 → 14 12月 2020 |
出版系列
姓名 | 2020 IEEE 6th International Conference on Computer and Communications, ICCC 2020 |
---|
会议
会议 | 6th IEEE International Conference on Computer and Communications, ICCC 2020 |
---|---|
国家/地区 | 中国 |
市 | Chengdu |
时期 | 11/12/20 → 14/12/20 |
指纹
探究 'Event Detection in Soccer Video Based on Self-Attention' 的科研主题。它们共同构成独一无二的指纹。引用此
Ma, S., Shao, E., Xie, X., & Liu, W. (2020). Event Detection in Soccer Video Based on Self-Attention. 在 2020 IEEE 6th International Conference on Computer and Communications, ICCC 2020 (页码 1852-1856). 文章 9344896 (2020 IEEE 6th International Conference on Computer and Communications, ICCC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCC51575.2020.9344896