Survey of Spatio-Temporal Interest Point Detection Algorithms in Video

doi:10.1109/ACCESS.2017.2712789

OPT OpenIR > 光谱成像技术研究室

	Survey of Spatio-Temporal Interest Point Detection Algorithms in Video
	Li, Yanshan 1; Xia, Rongjie 1; Huang, Qinghua 2,3,4; Xie, Weixin 1; Li, Xuelong 5; Huang, QH (reprint author), Shenzhen Univ, Coll Informat Engn, Shenzhen 518060, Peoples R China.
作者部门	光学影像学习与分析中心
	2017
发表期刊	IEEE ACCESS
ISSN	2169-3536
卷号	5 页码:10323-10331
产权排序	5
摘要	Recently, increasing attention has been paid to the detection of spatio-temporal interest points (STIPs), which has become a key technique and research focus in the field of computer vision. Its applications include human action recognition, video surveillance, video summarization, and content based video retrieval. Amount of work has been done by many researchers in STIP detection. This paper presents a comprehensive review on STIP detection algorithms. We first propose the detailed introductions and analysis of the existing STIP detection algorithms. STIP detection algorithms are robust in detecting interest points for video in the spatio-temporal domain Next, we summarize the existing challenges in the STIP detection for video, such as low time efficiency, poor robustness with respect to camera movement, illumination change, perspective occlusion, and background clutter. This paper also presents the application situations of STIP and discusses the potential development trends of STIP detection.
文章类型	Article
关键词	Video Spatio-temporal Interest Point (Stip) Local Invariant Feature Stip Detection Algorithm
学科领域	Computer Science, Information Systems
WOS标题词	Science & Technology ; Technology
DOI	10.1109/ACCESS.2017.2712789
收录类别	SCI ; EI
关键词[WOS]	INVARIANT FEATURE TRANSFORM ; MULTISPECTRAL IMAGE ; ACTION RECOGNITION ; ANOMALY DETECTION ; SCALE ; FEATURES ; SIFT
语种	英语
WOS研究方向	Computer Science ; Engineering ; Telecommunications
项目资助者	National Natural Science Foundation of China(61401286 ; Foundation for Distinguished Young Talents in Higher Education of Guangdong(2014KQNCX132) ; Shenzhen Science and Technology Project(JCYJ20160307143441261) ; National Defense Preliminary Research Project(9140C80050215 0C80341) ; Guangzhou Key Lab of Body Data Science(201605030011) ; Guangdong Provincial Science and Technology Program International Collaborative Projects(2014A050503020) ; 61372007 ; 61571193)
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000404360000027
引用统计	被引频次：36[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/29103
专题	光谱成像技术研究室
通讯作者	Huang, QH (reprint author), Shenzhen Univ, Coll Informat Engn, Shenzhen 518060, Peoples R China.
作者单位	1.Shenzhen Univ, ATR Natl Key Lab Def Technol, Shenzhen 518060, Peoples R China 2.Shenzhen Univ, Coll Informat Engn, Shenzhen 518060, Peoples R China 3.South China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China 4.Northwestern Polytech Univ, Ctr Opt Imagery Anal & Learning OPTIMAL, Sch Elect & Informat, Xian 710072, Peoples R China 5.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Li, Yanshan,Xia, Rongjie,Huang, Qinghua,et al. Survey of Spatio-Temporal Interest Point Detection Algorithms in Video[J]. IEEE ACCESS,2017,5:10323-10331.
APA	Li, Yanshan,Xia, Rongjie,Huang, Qinghua,Xie, Weixin,Li, Xuelong,&Huang, QH .(2017).Survey of Spatio-Temporal Interest Point Detection Algorithms in Video.IEEE ACCESS,5,10323-10331.
MLA	Li, Yanshan,et al."Survey of Spatio-Temporal Interest Point Detection Algorithms in Video".IEEE ACCESS 5(2017):10323-10331.

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