CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术研究
Surveillance video synopsis in the compressed domain for fast video browsing
Wang, Shi-zheng1,2; Wang, Zhong-yuan1; Hu, Rui-min1
Source PublicationJOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
2013-11-01
Volume24Issue:8Pages:1431-1442
SubtypeArticle
AbstractThe traditional pixel-domain based video analysis methods have taken dominated places for long. However, due to the rapidly increasing volume and resolution of surveillance video, the desirable fast and scalable browsing encounters significant challenges in terms of efficiency and flexibility. Under this circumstance, operating surveillance video in compressed domain has aroused great concern in academy and industry. In order to perform the intelligent video analysis task on the premise of preserving accuracy and controlling complexity, this paper presents a compressed-domain approach for massive surveillance video synopsis generation, labeling and browsing. The main work and achievements include: (1) a compressed-domain scheme is established to condense the compressed surveillance video and record the synopsis results; (2) a background modeling method via the Motion Vector based Local Binary Pattern (MVLBP) is introduced to extract moving objects in an efficient way; (3) an object flags based synopsis labeling method is proposed to represent the object regions as well as their display modes in a flexible way. Experimental results show that the video analysis system based on this framework can provide not only efficient synopsis generation but also flexible scalable or playback browsing. (C) 2013 Elsevier Inc. All rights reserved.
KeywordSurveillance Video Compressed Domain Video Synopsis Video Labeling Scalable Browsing Fast Browsing Background Modeling Intelligent Video
WOS HeadingsScience & Technology ; Technology
WOS KeywordMOVING OBJECT SEGMENTATION ; VISUAL SURVEILLANCE ; CLASSIFICATION ; FRAMES ; MODEL
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering
WOS IDWOS:000328590700017
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8938
Collection模式识别国家重点实验室_生物识别与安全技术研究
Affiliation1.Wuhan Univ, Wuhan 430072, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wang, Shi-zheng,Wang, Zhong-yuan,Hu, Rui-min. Surveillance video synopsis in the compressed domain for fast video browsing[J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,2013,24(8):1431-1442.
APA Wang, Shi-zheng,Wang, Zhong-yuan,&Hu, Rui-min.(2013).Surveillance video synopsis in the compressed domain for fast video browsing.JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,24(8),1431-1442.
MLA Wang, Shi-zheng,et al."Surveillance video synopsis in the compressed domain for fast video browsing".JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 24.8(2013):1431-1442.
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