YNAO OpenIR  > 天文技术实验室
Identifying players in broadcast videos using graph convolutional network
Feng Tao1; Ji KF(季凯帆)2; Bian Ang1; Liu Chang3; Zhang Jianzhou1
发表期刊Pattern Recognition
2022-04
卷号124
DOI10.1016/j.patcog.2021.108503
产权排序第2完成单位
收录类别SCI ; EI
关键词Graph representation learning Graph embedding Pre-trained model Player identification
摘要

The person representation problem is a critical bottleneck in the player identification task. However, the current approaches for player identification utilizing the entire image features only are not sufficient to preserve identities due to the reliance on visible visual representations. In this paper, we propose a novel player representation method using a graph-powered pose representation to resolve this bottleneck problem. Our framework consists of three modules: (i.) a novel pose-guided representation module that is able to capture the pose changes dynamically and their associated effects; (ii.) a pose-guided graph embedding module using both the image deep features and the pose structure information for a better player representation inference; (iii.) an identification module as a player classifier. Experiment results on the real-world sport game scenarios demonstrate that our method achieves state-of-the-art identification performance, together with a better player representation.

资助项目N/A
项目资助者N/A
语种英语
学科领域计算机科学技术 ; 人工智能 ; 模式识别 ; 计算机应用
学科门类工学 ; 工学::计算机科学与技术(可授工学、理学学位)
文章类型Article
出版者ELSEVIER SCI LTD
出版地THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
ISSN0031-3203
URL查看原文
WOS记录号WOS:000740181700002
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
关键词[WOS]NEURAL-NETWORK
EI入藏号20215311410246
EI主题词Computer vision
EI分类号723.4 Artificial Intelligence - 723.5 Computer Applications - 741.2 Vision
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ynao.ac.cn/handle/114a53/24753
专题天文技术实验室
通讯作者Bian Ang
作者单位1.College of Computer Science, Sichuan University, Chengdu, China
2.Yunnan Observatory, Chinese Academy of Sciences, Kunming, China
3.School of Biological Science and Medical Engineering, Beihang University, Beijing, China
推荐引用方式
GB/T 7714
Feng Tao,Ji KF,Bian Ang,et al. Identifying players in broadcast videos using graph convolutional network[J]. Pattern Recognition,2022,124.
APA Feng Tao,Ji KF,Bian Ang,Liu Chang,&Zhang Jianzhou.(2022).Identifying players in broadcast videos using graph convolutional network.Pattern Recognition,124.
MLA Feng Tao,et al."Identifying players in broadcast videos using graph convolutional network".Pattern Recognition 124(2022).
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Identifying players (3998KB)期刊论文出版稿开放获取CC BY-NC-SA浏览 请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Feng Tao]的文章
[Ji KF(季凯帆)]的文章
[Bian Ang]的文章
百度学术
百度学术中相似的文章
[Feng Tao]的文章
[Ji KF(季凯帆)]的文章
[Bian Ang]的文章
必应学术
必应学术中相似的文章
[Feng Tao]的文章
[Ji KF(季凯帆)]的文章
[Bian Ang]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Identifying players in broadcast videos using graph convolutional network.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。