Video Compression and Retrieval of Moving Object Location Applied to Surveillance

被引:0
|
作者
Schwartz, William Robson [1 ]
Pedrini, Helio [2 ]
Davis, Larry S. [1 ]
机构
[1] Univ Maryland, Dept Comp Sci, College Pk, MD 20742 USA
[2] Univ Estadual Campinas, Inst Comp, Campinas, SP 13084971, Brazil
基金
巴西圣保罗研究基金会;
关键词
PCA;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A major problem in surveillance systems is the storage requirements for video archival; videos are recorded continuously for long periods of time, resulting in large amounts of data. Therefore, it is essential to apply efficient compression techniques. Additionally, it is useful to be able to index the archived videos based on events. In general, such events are defined by the interaction among moving objects in the scene. Consequently, besides data compression, efficient ways of storing moving objects Should be considered. We present a method that exploits both temporal and spatial redundancy of videos captured from static cameras to perform compression and subsequently allows fast retrieval of moving object locations directly from the compressed data. Experimental results show that the approach achieves high compression ratios compared to other existing video compression techniques without significant quality degradation and is fast clue to the simplicity of the operations required for compression and decompression.
引用
收藏
页码:906 / +
页数:2
相关论文
共 50 条
  • [1] Moving Objects Representation for Object Based Surveillance Video Retrieval System
    Han, Jianping
    Tan, Tian
    Chen, Longfei
    Zhang, Daxing
    [J]. INTERNATIONAL JOURNAL OF SECURITY AND ITS APPLICATIONS, 2014, 8 (02): : 315 - 322
  • [2] Video surveillance systems for moving object
    Merkishin, G., V
    Medvedev, S., V
    [J]. 2006 16TH INTERNATIONAL CRIMEAN CONFERENCE MICROWAVE & TELECOMMUNICATION TECHNOLOGY, VOLS 1 AND 2, CONFERENCE PROCEEDINGS, 2006, : 497 - +
  • [3] Multispectral object segmentation and retrieval in surveillance video
    Conaire, C. O.
    O'Connor, N. E.
    Cooke, E.
    Smeaton, A. F.
    [J]. 2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS, 2006, : 2381 - +
  • [5] Relevance Feedback for Surveillance Video Retrieval at Object Level
    Thi-Lan Le
    [J]. FUTURE INFORMATION TECHNOLOGY, PT II, 2011, 185 : 175 - 182
  • [6] Moving Object Detection for Content Based Video Retrieval
    Raviprakash, Nitya
    Suresh, Meggha
    Rathis, Asmitha
    Devarla, Divija
    Yadav, Aakanksha
    Nagaraja, G. S.
    [J]. 2016 INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP), VOL. 1, 2016, : 322 - 326
  • [7] Moving Object Detection and Shadow Removal in Video Surveillance
    Yan, Tinggui
    Hu, Shaohua
    Su, Xiaofeng
    He, Xinhua
    [J]. PROCEEDINGS OF 2016 10TH INTERNATIONAL CONFERENCE ON SOFTWARE, KNOWLEDGE, INFORMATION MANAGEMENT & APPLICATIONS (SKIMA), 2016, : 3 - 8
  • [8] Moving object segmentation for video surveillance and conferencing applications
    Alsaqre, FE
    Yuan, BZ
    [J]. 2003 INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY, VOL 1 AND 2, PROCEEDINGS, 2003, : 1856 - 1859
  • [9] An efficient moving object extraction algorithm for video surveillance
    Wang, DJ
    Chen, TH
    Chiou, YC
    Liau, HS
    [J]. KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 3, PROCEEDINGS, 2005, 3683 : 346 - 352
  • [10] Hybrid Method for Moving Object Exploration in Video Surveillance
    Krishna, R. Sathya Bama
    Bharathi, B.
    Ahamed, Mohamed Uvaze A.
    Ankayarkanni, B.
    [J]. PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND KNOWLEDGE ECONOMY (ICCIKE' 2019), 2019, : 773 - 778