FSD-10: A fine-grained classification dataset for figure skating

doi:10.1016/j.neucom.2020.06.108

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	FSD-10: A fine-grained classification dataset for figure skating
	Liu, Shenglan 1,2; Liu, Xiang 1; Huang, Gao 3; Qiao, Hong4 ; Hu, Lianyu 1; Jiang, Dong 1; Zhang, Aibin 1; Liu, Yang 1; Guo, Ge 1
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
	2020-11-06
卷号	413 页码:360-367
通讯作者	Liu, Shenglan(liusl@mail.dlut.edu.cn)
摘要	Action recognition is an important and challenging problem in video analysis. Although the past decade has witnessed progress in action recognition with the development of deep learning, such process has been slow in competitive sports content analysis. To promote the research on action recognition from competitive sports video clips, we introduce a Figure Skating Dataset (FSD-10) for fine-grained sports content analysis. To this end, we collect 1484 clips from the worldwide figure skating championships in 2017-2018, which consist of 10 different actions in men/ladies programs. Each clip is at a rate of 30 frames per second with resolution 1080 x 720, which are annotated by experts. To build a baseline for action recognition in figure skating, we evaluate state-of-the-art action recognition methods on FSD-10. Motivated by the idea that domain knowledge is of great concern in sports field, we propose a key-frame based temporal segment network (KTSN) for classification and achieve remarkable performance. Experimental results demonstrate that FSD-10 is an ideal dataset for benchmarking action recognition algorithms, as it requires to accurately extract action motions rather than action poses. We hope FSD-10, which is designed to have a large collection of finegrained actions, can serve as a new challenge to develop more robust and advanced action recognition models. (C) 2020 Elsevier B.V. All rights reserved.
关键词	Action recognition Figure Skating Dataset Fine-grained sports content analysis Keyframe based temporal segment network
DOI	10.1016/j.neucom.2020.06.108
关键词[WOS]	ACTION RECOGNITION
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2017YFB1300200] ; National Key Research and Development Program of China[2017YFB1300203] ; Fundamental Research Funds for the Central Universities[DUT20RC(5)010]
项目资助者	National Key Research and Development Program of China ; Fundamental Research Funds for the Central Universities
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000579803700030
出版者	ELSEVIER
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/42173
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Liu, Shenglan
作者单位	1.Dalian Univ Technol, Sch Innovat & Entrepreneurship, Dalian, Liaoning, Peoples R China 2.Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian, Liaoning, Peoples R China 3.Tsinghua Univ, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Liu, Shenglan,Liu, Xiang,Huang, Gao,et al. FSD-10: A fine-grained classification dataset for figure skating[J]. NEUROCOMPUTING,2020,413:360-367.
APA	Liu, Shenglan.,Liu, Xiang.,Huang, Gao.,Qiao, Hong.,Hu, Lianyu.,...&Guo, Ge.(2020).FSD-10: A fine-grained classification dataset for figure skating.NEUROCOMPUTING,413,360-367.
MLA	Liu, Shenglan,et al."FSD-10: A fine-grained classification dataset for figure skating".NEUROCOMPUTING 413(2020):360-367.