Motion segmentation-based surveillance video compression using adaptive particle swarm optimization

Video surveillance is one of the widely used and most active research applications of computer vision. Although lots of works have been done in the area of smart surveillance, but still there is a need of effective compression technique for compact archival and efficient transmission of vast amount...

Full description

Saved in:

Bibliographic Details
Published in:	Neural computing & applications Vol. 32; no. 15; pp. 11443 - 11457
Main Authors:	Sengar, Sandeep Singh, Mukhopadhyay, Susanta
Format:	Journal Article
Language:	English
Published:	London Springer London 01.08.2020 Springer Nature B.V
Subjects:	Artificial Intelligence Change detection Coding Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer vision Data Mining and Knowledge Discovery Huffman codes Image Processing and Computer Vision Image segmentation Motion compensation Motion simulation Optical flow (image analysis) Original Article Particle swarm optimization Probability and Statistics in Computer Science Segmentation Surveillance Video compression Video data Video transmission Segmentation Motion estimation Particle swarm optimization Optical flow
ISSN:	0941-0643, 1433-3058
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	Video surveillance is one of the widely used and most active research applications of computer vision. Although lots of works have been done in the area of smart surveillance, but still there is a need of effective compression technique for compact archival and efficient transmission of vast amount of surveillance video data. In this work, we propose a hybrid video compression approach with the help of foreground motion compensation for the above application. This method works effectively by including the advantages of both block-based and object-based coding techniques as well as reducing the drawbacks of both. The proposed method first segments the foreground moving objects from the background with the help of adaptive thresholding-based optical flow techniques. Next, it determines the contour of the segmented foreground regions with the help of Freeman chain code. Subsequently, block-based motion estimation and compensation using variants of particle swarm optimization are computed. After that, motion failure areas are detected using change detection method, and finally, DCT and Huffman coding-based entropy encoding are done to compactly represent the data. Experimental results and analyses on different surveillance video sequences using Wilcoxon’s rank-sum test, PSNR and SSID show that our method outperforms other recent and relevant existing techniques.
AbstractList	Video surveillance is one of the widely used and most active research applications of computer vision. Although lots of works have been done in the area of smart surveillance, but still there is a need of effective compression technique for compact archival and efficient transmission of vast amount of surveillance video data. In this work, we propose a hybrid video compression approach with the help of foreground motion compensation for the above application. This method works effectively by including the advantages of both block-based and object-based coding techniques as well as reducing the drawbacks of both. The proposed method first segments the foreground moving objects from the background with the help of adaptive thresholding-based optical flow techniques. Next, it determines the contour of the segmented foreground regions with the help of Freeman chain code. Subsequently, block-based motion estimation and compensation using variants of particle swarm optimization are computed. After that, motion failure areas are detected using change detection method, and finally, DCT and Huffman coding-based entropy encoding are done to compactly represent the data. Experimental results and analyses on different surveillance video sequences using Wilcoxon’s rank-sum test, PSNR and SSID show that our method outperforms other recent and relevant existing techniques.
Author	Mukhopadhyay, Susanta Sengar, Sandeep Singh
Author_xml	– sequence: 1 givenname: Sandeep Singh orcidid: 0000-0003-2171-9332 surname: Sengar fullname: Sengar, Sandeep Singh email: sandeepsingh.s@srmap.edu.in organization: Department of Computer Science and Engineering, SRM University-AP – sequence: 2 givenname: Susanta surname: Mukhopadhyay fullname: Mukhopadhyay, Susanta organization: Department of Computer Science and Engineering, Indian Institute of Technology (ISM)
BookMark	eNp9kE1LAzEQhoNUsK3-AU8Lnlcnn5sepfgFFS96Dmk6W1J2N2uyreivd9cVBA89DTN5npnwzsikCQ0ScknhmgIUNwlAMpoDXeQgFJe5OiFTKjjPOUg9IVNYiP5ZCX5GZintAHpMyylxz6HzockSbmtsOjs0-dom3GRpHw_oq8o2DrOD32DIXKjbiCkNxj75ZpvZjW07f8CstbHzrsIsfdhYZ6Gf1v7rZ985OS1tlfDit87J2_3d6_IxX708PC1vV7njouhyBpZpSzWUYCnnSoF2khe81NKJBTo7zBRbAy-Ql9JaXRSwYUw6VqxRrPmcXI172xje95g6swv72PQnDWdUS1FwrY5RTDAhlVCU9ZQeKRdDShFL4_yYThetrwwFMwRvxuBNH7z5Cd4MB9g_tY2-tvHzuMRHKfVws8X496sj1jdXSJg4
CitedBy_id	crossref_primary_10_3390_electronics10243116 crossref_primary_10_1038_s41598_023_36066_8 crossref_primary_10_3390_make5040067 crossref_primary_10_1109_TBC_2024_3434736 crossref_primary_10_1109_TIV_2023_3267443 crossref_primary_10_1016_j_displa_2023_102454 crossref_primary_10_1109_LGRS_2022_3157978 crossref_primary_10_1155_2023_8891239 crossref_primary_10_3390_s25103101 crossref_primary_10_1007_s11042_024_20016_1 crossref_primary_10_1109_ACCESS_2025_3580151 crossref_primary_10_1007_s41870_023_01606_y crossref_primary_10_1007_s00138_020_01126_w crossref_primary_10_1109_MMUL_2023_3289953 crossref_primary_10_4018_IJISP_347878 crossref_primary_10_1016_j_neucom_2022_02_072 crossref_primary_10_1007_s11042_022_13484_w crossref_primary_10_1155_2023_5596605 crossref_primary_10_1002_ima_22982 crossref_primary_10_1007_s11227_022_04412_8 crossref_primary_10_1109_TBC_2023_3280039 crossref_primary_10_1007_s41870_023_01456_8 crossref_primary_10_1007_s10514_020_09964_3 crossref_primary_10_1007_s11042_022_12522_x crossref_primary_10_1109_ACCESS_2023_3248067 crossref_primary_10_1145_3744649 crossref_primary_10_1007_s42979_023_01693_5 crossref_primary_10_1007_s11042_022_13388_9
Cites_doi	10.1016/j.neucom.2014.08.062 10.1016/j.patcog.2004.08.017 10.1109/TCSVT.2011.2138750 10.1016/j.cviu.2015.10.014 10.1016/j.image.2011.01.002 10.1109/ICIINFS.2011.6038044 10.1109/PCS.2015.7170091 10.1109/TCSVT.2009.2017074 10.1016/j.ijleo.2016.03.061 10.1007/s11760-017-1093-8 10.1109/TCSVT.2009.2031442 10.1109/TCSVT.2009.2020253 10.1007/s00034-017-0613-7 10.1109/ICASSP.2010.5495033 10.1109/TIP.2003.819861 10.1016/j.jvcir.2016.05.016 10.1016/j.swevo.2011.02.002 10.1007/s00521-010-0503-4 10.1109/76.554433 10.1049/cp:19960864 10.1117/12.805596 10.1109/WiSPNET.2016.7566561 10.1016/j.jvcir.2015.11.014 10.1016/j.dsp.2012.05.006 10.1016/j.imavis.2013.04.004 10.1049/el.2015.3784 10.1109/TCSVT.2004.825536 10.1109/RAIT.2016.7507946 10.1007/s00521-016-2363-z 10.1109/83.806627 10.1109/QSHINE.2014.6928652 10.1016/j.engappai.2013.04.003 10.1109/ICIP.2017.8296286 10.1109/TSMCC.2004.829274 10.1007/978-3-030-01237-3_26 10.1007/s12555-010-0501-4 10.1016/j.ijleo.2017.07.040 10.1016/0004-3702(81)90024-2 10.1007/s00521-014-1640-y 10.1109/T-C.1974.223784 10.1117/3.501104 10.1007/s00521-016-2319-3 10.1109/MMSP.2015.7340838 10.1007/978-3-642-32894-7_27 10.1007/s00521-012-0905-6 10.1109/NABIC.2009.5393690 10.1007/978-3-030-19823-7_51 10.1016/j.sigpro.2016.10.015 10.1109/ICC.2007.440 10.1016/j.eswa.2015.04.026 10.1007/s00521-012-1003-5 10.1016/j.jvcir.2017.08.007 10.1016/j.image.2015.03.009 10.1016/j.ins.2014.01.003 10.1007/s13369-017-2672-2 10.1080/0952813X.2015.1042530 10.1016/j.rti.2005.04.008 10.1109/TBC.2011.2170611 10.1016/j.aeue.2014.02.011 10.1016/0196-6774(85)90036-7 10.1109/TCSVT.2011.2148490 10.1109/SPIN.2015.7095310 10.1109/TMM.2011.2127464 10.1117/12.863522 10.1016/j.asoc.2016.03.022 10.1016/j.ins.2012.02.014 10.1016/j.asoc.2012.09.020
ContentType	Journal Article
Copyright	Springer-Verlag London Ltd., part of Springer Nature 2019 Springer-Verlag London Ltd., part of Springer Nature 2019. Copyright Springer Nature B.V. Aug 2020
Copyright_xml	– notice: Springer-Verlag London Ltd., part of Springer Nature 2019 – notice: Springer-Verlag London Ltd., part of Springer Nature 2019. – notice: Copyright Springer Nature B.V. Aug 2020
DBID	AAYXX CITATION 8FE 8FG AFKRA ARAPS BENPR BGLVJ CCPQU DWQXO HCIFZ P5Z P62 PHGZM PHGZT PKEHL PQEST PQGLB PQQKQ PQUKI PRINS
DOI	10.1007/s00521-019-04635-6
DatabaseName	CrossRef ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central UK/Ireland Advanced Technologies & Aerospace Database‎ (1962 - current) ProQuest Central ProQuest Technology Collection ProQuest One ProQuest Central Korea SciTech Premium Collection Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Proquest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China
DatabaseTitle	CrossRef Advanced Technologies & Aerospace Collection Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest One Academic Eastern Edition SciTech Premium Collection ProQuest One Community College ProQuest Technology Collection ProQuest SciTech Collection ProQuest Central China ProQuest Central Advanced Technologies & Aerospace Database ProQuest One Applied & Life Sciences ProQuest One Academic UKI Edition ProQuest Central Korea ProQuest Central (New) ProQuest One Academic ProQuest One Academic (New)
DatabaseTitleList	Advanced Technologies & Aerospace Collection Advanced Technologies & Aerospace Collection
Database_xml	– sequence: 1 dbid: P5Z name: Advanced Technologies & Aerospace Database url: https://search.proquest.com/hightechjournals sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Computer Science
EISSN	1433-3058
EndPage	11457
ExternalDocumentID	10_1007_s00521_019_04635_6
GroupedDBID	-Y2 -~C .4S .86 .DC .VR 06D 0R~ 0VY 123 1N0 1SB 2.D 203 28- 29N 2J2 2JN 2JY 2KG 2LR 2P1 2VQ 2~H 30V 4.4 406 408 409 40D 40E 53G 5QI 5VS 67Z 6NX 8FE 8FG 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAOBN AAPKM AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBRH ABBXA ABDBE ABDBF ABDZT ABECU ABFSG ABFTD ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABLJU ABMNI ABMQK ABNWP ABQBU ABQSL ABRTQ ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACSNA ACSTC ACUHS ACZOJ ADHHG ADHIR ADHKG ADIMF ADKFA ADKNI ADKPE ADMLS ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AEZWR AFBBN AFDZB AFEXP AFGCZ AFHIU AFKRA AFLOW AFOHR AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGQPQ AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHPBZ AHSBF AHWEU AHYZX AIAKS AIGIU AIIXL AILAN AITGF AIXLP AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARAPS ARCSS ARMRJ ASPBG ATHPR AVWKF AXYYD AYFIA AYJHY AZFZN B-. B0M BA0 BBWZM BDATZ BENPR BGLVJ BGNMA BSONS CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 EAD EAP EBLON EBS ECS EDO EIOEI EJD EMI EMK EPL ESBYG EST ESX F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNWQR GQ7 GQ8 GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I-F I09 IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV KOW LAS LLZTM M4Y MA- N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM P19 P2P P62 P9O PF0 PHGZM PHGZT PQGLB PT4 PT5 QOK QOS R4E R89 R9I RHV RIG RNI RNS ROL RPX RSV RZK S16 S1Z S26 S27 S28 S3B SAP SCJ SCLPG SCO SDH SDM SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 ZMTXR ~8M ~EX AAYXX AFFHD CITATION DWQXO PKEHL PQEST PQQKQ PQUKI PRINS
ID	FETCH-LOGICAL-c347t-20a28a180f0a1336608c5373f85c49eca336662b037e3f5aa8770d225c27be4b3
IEDL.DBID	BENPR
ISICitedReferencesCount	29
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000500866600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0941-0643
IngestDate	Wed Nov 05 06:24:52 EST 2025 Wed Nov 05 00:35:23 EST 2025 Sat Nov 29 07:45:38 EST 2025 Tue Nov 18 22:35:46 EST 2025 Mon Jul 21 06:07:21 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	15
Keywords	Segmentation Motion estimation Particle swarm optimization Optical flow
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c347t-20a28a180f0a1336608c5373f85c49eca336662b037e3f5aa8770d225c27be4b3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0003-2171-9332
PQID	2424564612
PQPubID	2043988
PageCount	15
ParticipantIDs	proquest_journals_3218547386 proquest_journals_2424564612 crossref_citationtrail_10_1007_s00521_019_04635_6 crossref_primary_10_1007_s00521_019_04635_6 springer_journals_10_1007_s00521_019_04635_6
PublicationCentury	2000
PublicationDate	20200800 2020-08-00 20200801
PublicationDateYYYYMMDD	2020-08-01
PublicationDate_xml	– month: 8 year: 2020 text: 20200800
PublicationDecade	2020
PublicationPlace	London
PublicationPlace_xml	– name: London – name: Heidelberg
PublicationTitle	Neural computing & applications
PublicationTitleAbbrev	Neural Comput & Applic
PublicationYear	2020
Publisher	Springer London Springer Nature B.V
Publisher_xml	– name: Springer London – name: Springer Nature B.V
References	4635_CR38 BKP Horn (4635_CR52) 1981; 17 SS Sengar (4635_CR13) 2017; 145 BP Bondzulic (4635_CR64) 2016; 52 SS Sengar (4635_CR14) 2016; 127 4635_CR30 Y-M Chen (4635_CR36) 2011; 13 F Porikli (4635_CR37) 2010; 20 W Lin (4635_CR34) 2012; 58 Z Zhu (4635_CR20) 2012; 22 X Guo (4635_CR22) 2016; 39 DE Knuth (4635_CR12) 1985; 6 J Sum (4635_CR10) 2013; 22 L Liu (4635_CR68) 2009; 19 SS Sengar (4635_CR7) 2017; 49 ER Dougherty (4635_CR54) 2003 J Derrac (4635_CR61) 2011; 1 IS Kim (4635_CR6) 2010; 8 4635_CR39 4635_CR48 SIA Pandian (4635_CR49) 2013; 26 4635_CR46 S Mirjalili (4635_CR60) 2014; 25 4635_CR43 AC Nazare Jr (4635_CR2) 2016; 144 4635_CR41 DJ Hemanth (4635_CR55) 2018; 37 4635_CR40 Z Wang (4635_CR65) 2004; 13 YK Liu (4635_CR15) 2005; 38 RV Babu (4635_CR31) 2004; 14 SS Sengar (4635_CR9) 2017; 11 FFE Guraya (4635_CR4) 2015; 149 W Zeng (4635_CR33) 2005; 11 J Cai (4635_CR53) 2012; 197 X-B Meng (4635_CR59) 2016; 28 4635_CR57 YK Baik (4635_CR51) 2013; 31 4635_CR56 N Ahmed (4635_CR11) 1974; 100 D Liu (4635_CR45) 2010; 20 Y-M Chen (4635_CR35) 2011; 21 M Hollander (4635_CR63) 2013 D Chen (4635_CR16) 2011; 20 Y Li (4635_CR18) 2015; 35 W Hu (4635_CR5) 2004; 34 M Al-Nawashi (4635_CR3) 2017; 28 H Bhaumik (4635_CR8) 2016; 46 E Cuevas (4635_CR21) 2013; 13 4635_CR27 4635_CR26 M Paul (4635_CR44) 2011; 21 4635_CR25 E Tzoreff (4635_CR32) 2017; 133 4635_CR24 4635_CR67 4635_CR66 MT Mahmoudi (4635_CR29) 2013; 22 X-B Meng (4635_CR58) 2015; 42 JD Gibbons (4635_CR62) 2011 P He (4635_CR69) 2016; 35 K Belloulata (4635_CR17) 2014; 68 X Jin (4635_CR42) 2011; 26 SS Sengar (4635_CR47) 2017; 42 Z Wang (4635_CR1) 2017; 28 M Gallant (4635_CR23) 1999; 8 MK Lim (4635_CR50) 2014; 283 R Talluri (4635_CR19) 1997; 7 4635_CR28
References_xml	– volume: 149 start-page: 1348 year: 2015 ident: 4635_CR4 publication-title: Neurocomputing doi: 10.1016/j.neucom.2014.08.062 – volume: 38 start-page: 553 issue: 4 year: 2005 ident: 4635_CR15 publication-title: Pattern Recognit doi: 10.1016/j.patcog.2004.08.017 – volume: 21 start-page: 1242 issue: 9 year: 2011 ident: 4635_CR44 publication-title: IEEE Trans Circuits Syst Video Technol doi: 10.1109/TCSVT.2011.2138750 – volume: 144 start-page: 258 year: 2016 ident: 4635_CR2 publication-title: Comput Vis Image Underst doi: 10.1016/j.cviu.2015.10.014 – volume: 26 start-page: 130 issue: 3 year: 2011 ident: 4635_CR42 publication-title: Signal Process Image Commun doi: 10.1016/j.image.2011.01.002 – ident: 4635_CR28 doi: 10.1109/ICIINFS.2011.6038044 – ident: 4635_CR38 doi: 10.1109/PCS.2015.7170091 – volume: 19 start-page: 453 issue: 4 year: 2009 ident: 4635_CR68 publication-title: IEEE Trans Circuits Syst Video Technol doi: 10.1109/TCSVT.2009.2017074 – volume: 127 start-page: 6258 issue: 16 year: 2016 ident: 4635_CR14 publication-title: Int J Light Electron Opt doi: 10.1016/j.ijleo.2016.03.061 – volume: 11 start-page: 1 issue: 7 year: 2017 ident: 4635_CR9 publication-title: Signal Image Video Process doi: 10.1007/s11760-017-1093-8 – volume: 20 start-page: 325 issue: 3 year: 2010 ident: 4635_CR45 publication-title: IEEE Trans Circuits Syst Video Technol doi: 10.1109/TCSVT.2009.2031442 – volume: 20 start-page: 2 issue: 1 year: 2010 ident: 4635_CR37 publication-title: IEEE Trans Circuits Syst Video Technol doi: 10.1109/TCSVT.2009.2020253 – volume: 37 start-page: 1609 issue: 4 year: 2018 ident: 4635_CR55 publication-title: Circuits Syst Signal Process doi: 10.1007/s00034-017-0613-7 – ident: 4635_CR43 doi: 10.1109/ICASSP.2010.5495033 – volume: 13 start-page: 600 issue: 4 year: 2004 ident: 4635_CR65 publication-title: IEEE Trans Image Process doi: 10.1109/TIP.2003.819861 – volume: 39 start-page: 164 year: 2016 ident: 4635_CR22 publication-title: J Vis Commun Image Represent doi: 10.1016/j.jvcir.2016.05.016 – volume: 1 start-page: 3 issue: 1 year: 2011 ident: 4635_CR61 publication-title: Swarm Evolut Comput doi: 10.1016/j.swevo.2011.02.002 – volume-title: Nonparametric statistical inference year: 2011 ident: 4635_CR62 – volume: 20 start-page: 171 issue: 2 year: 2011 ident: 4635_CR16 publication-title: Neural Comput Appl doi: 10.1007/s00521-010-0503-4 – volume: 7 start-page: 221 issue: 1 year: 1997 ident: 4635_CR19 publication-title: IEEE Trans Circuits Syst Video Technol doi: 10.1109/76.554433 – ident: 4635_CR24 doi: 10.1049/cp:19960864 – ident: 4635_CR39 doi: 10.1117/12.805596 – ident: 4635_CR40 doi: 10.1109/WiSPNET.2016.7566561 – volume: 35 start-page: 55 year: 2016 ident: 4635_CR69 publication-title: J Vis Commun Image Represent doi: 10.1016/j.jvcir.2015.11.014 – volume: 22 start-page: 954 issue: 6 year: 2012 ident: 4635_CR20 publication-title: Digit Signal Process doi: 10.1016/j.dsp.2012.05.006 – volume: 31 start-page: 565 issue: 8 year: 2013 ident: 4635_CR51 publication-title: Image Vis Comput doi: 10.1016/j.imavis.2013.04.004 – volume: 52 start-page: 454 issue: 6 year: 2016 ident: 4635_CR64 publication-title: Electron Lett doi: 10.1049/el.2015.3784 – volume: 14 start-page: 462 issue: 4 year: 2004 ident: 4635_CR31 publication-title: IEEE Trans Circuits Syst Video Technol doi: 10.1109/TCSVT.2004.825536 – ident: 4635_CR48 doi: 10.1109/RAIT.2016.7507946 – volume: 28 start-page: 565 issue: 1 year: 2017 ident: 4635_CR3 publication-title: Neural Comput Appl doi: 10.1007/s00521-016-2363-z – volume-title: Nonparametric statistical methods year: 2013 ident: 4635_CR63 – volume: 8 start-page: 1816 issue: 12 year: 1999 ident: 4635_CR23 publication-title: IEEE Trans Image Process doi: 10.1109/83.806627 – ident: 4635_CR26 doi: 10.1109/QSHINE.2014.6928652 – volume: 26 start-page: 1811 issue: 8 year: 2013 ident: 4635_CR49 publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2013.04.003 – ident: 4635_CR67 doi: 10.1109/ICIP.2017.8296286 – volume: 34 start-page: 334 issue: 3 year: 2004 ident: 4635_CR5 publication-title: IEEE Trans Syst Man Cybern doi: 10.1109/TSMCC.2004.829274 – ident: 4635_CR66 doi: 10.1007/978-3-030-01237-3_26 – volume: 8 start-page: 926 issue: 5 year: 2010 ident: 4635_CR6 publication-title: Int J Control Autom Syst doi: 10.1007/s12555-010-0501-4 – volume: 145 start-page: 130 year: 2017 ident: 4635_CR13 publication-title: Optik doi: 10.1016/j.ijleo.2017.07.040 – volume: 17 start-page: 185 issue: 1–3 year: 1981 ident: 4635_CR52 publication-title: Artif intell doi: 10.1016/0004-3702(81)90024-2 – volume: 25 start-page: 1569 issue: 7–8 year: 2014 ident: 4635_CR60 publication-title: Neural Comput Appl doi: 10.1007/s00521-014-1640-y – volume: 100 start-page: 90 issue: 1 year: 1974 ident: 4635_CR11 publication-title: IEEE Trans Comput doi: 10.1109/T-C.1974.223784 – volume-title: Hands-on morphological image processing year: 2003 ident: 4635_CR54 doi: 10.1117/3.501104 – volume: 28 start-page: 127 issue: 1 year: 2017 ident: 4635_CR1 publication-title: Neural Comput Appl doi: 10.1007/s00521-016-2319-3 – ident: 4635_CR30 doi: 10.1109/MMSP.2015.7340838 – ident: 4635_CR57 doi: 10.1007/978-3-642-32894-7_27 – volume: 22 start-page: 1 issue: 1 year: 2013 ident: 4635_CR29 publication-title: Neural Comput Appl doi: 10.1007/s00521-012-0905-6 – ident: 4635_CR56 doi: 10.1109/NABIC.2009.5393690 – ident: 4635_CR27 doi: 10.1007/978-3-030-19823-7_51 – volume: 133 start-page: 32 year: 2017 ident: 4635_CR32 publication-title: Signal Process doi: 10.1016/j.sigpro.2016.10.015 – ident: 4635_CR46 doi: 10.1109/ICC.2007.440 – volume: 42 start-page: 6350 issue: 17–18 year: 2015 ident: 4635_CR58 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2015.04.026 – volume: 22 start-page: 1291 issue: 7–8 year: 2013 ident: 4635_CR10 publication-title: Neural Comput Appl doi: 10.1007/s00521-012-1003-5 – volume: 49 start-page: 89 year: 2017 ident: 4635_CR7 publication-title: J Vis Commun Image Represent doi: 10.1016/j.jvcir.2017.08.007 – volume: 35 start-page: 9 year: 2015 ident: 4635_CR18 publication-title: Signal Process Image Commun doi: 10.1016/j.image.2015.03.009 – volume: 283 start-page: 267 year: 2014 ident: 4635_CR50 publication-title: Inf Sci doi: 10.1016/j.ins.2014.01.003 – volume: 42 start-page: 3621 issue: 8 year: 2017 ident: 4635_CR47 publication-title: Arab J Sci Eng doi: 10.1007/s13369-017-2672-2 – volume: 28 start-page: 673 issue: 4 year: 2016 ident: 4635_CR59 publication-title: J Exp Theor Artif Intell doi: 10.1080/0952813X.2015.1042530 – volume: 11 start-page: 290 issue: 4 year: 2005 ident: 4635_CR33 publication-title: Real-Time Imaging doi: 10.1016/j.rti.2005.04.008 – volume: 58 start-page: 34 issue: 1 year: 2012 ident: 4635_CR34 publication-title: IEEE Trans Broadcast doi: 10.1109/TBC.2011.2170611 – volume: 68 start-page: 687 issue: 7 year: 2014 ident: 4635_CR17 publication-title: AEU-Int J Electron Commun doi: 10.1016/j.aeue.2014.02.011 – volume: 6 start-page: 163 issue: 2 year: 1985 ident: 4635_CR12 publication-title: J Algorithms doi: 10.1016/0196-6774(85)90036-7 – volume: 21 start-page: 1316 issue: 9 year: 2011 ident: 4635_CR35 publication-title: IEEE Trans Circuits Syst Video Technol doi: 10.1109/TCSVT.2011.2148490 – ident: 4635_CR25 doi: 10.1109/SPIN.2015.7095310 – volume: 13 start-page: 421 issue: 3 year: 2011 ident: 4635_CR36 publication-title: IEEE Trans Multimed doi: 10.1109/TMM.2011.2127464 – ident: 4635_CR41 doi: 10.1117/12.863522 – volume: 46 start-page: 1008 year: 2016 ident: 4635_CR8 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2016.03.022 – volume: 197 start-page: 53 year: 2012 ident: 4635_CR53 publication-title: Inf Sci doi: 10.1016/j.ins.2012.02.014 – volume: 13 start-page: 3047 issue: 6 year: 2013 ident: 4635_CR21 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2012.09.020
SSID	ssj0004685
Score	2.3710744
Snippet	Video surveillance is one of the widely used and most active research applications of computer vision. Although lots of works have been done in the area of...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	11443
SubjectTerms	Artificial Intelligence Change detection Coding Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer vision Data Mining and Knowledge Discovery Huffman codes Image Processing and Computer Vision Image segmentation Motion compensation Motion simulation Optical flow (image analysis) Original Article Particle swarm optimization Probability and Statistics in Computer Science Segmentation Surveillance Video compression Video data Video transmission
SummonAdditionalLinks	– databaseName: SpringerLINK Contemporary 1997-Present dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3LT8MgGCc6PXhxPuN0Gg7etEkHlMfRGBcPuhgfy24NpXQxce3SbvPfFxjd1EwTvRZomw--F3w_fgCcpypNsSAsoBEOTYKiRSASZIxhIhRKGCeZ4yLo37Fejw8G4sGDwqq62r0-knSWegF2szuYNvW1m_nGTQZ0HWwYd8etOj4-9T-hIR0Rp8lbbE0PwR4qs_odX93RMsb8dizqvE23-b__3AHbPrqEV_PlsAvWdL4HmjVzA_SKvA_UvSPvgZUejjz4KA-sQ0thNS1n2lIRmY7QgvQKaMvO5-WyObR18kMoUzm2dhKO_cqD1bssR7AwT0ce2XkAXro3z9e3gadbCBQmbGL0RSIuOzzMQmkyV0pDriLMcMYjRYRW0j6jKAkx0ziLpOSMhamxBwqxRJMEH4JGXuT6CEBBhU4oJkRn3EQokSRSasnSTsSyCGVhC3RqqcfK30VuKTHe4sUtyk6KsZFi7KQY0xa4WIwZz2_i-LV3u57M2GtlFSN3zEtMULeyGZtwx1IxczP6sp7bZfPPHzv-W_cTsIVs1u7KCNugMSmn-hRsqtnktSrP3GL-AC-J7Ys priority: 102 providerName: Springer Nature
Title	Motion segmentation-based surveillance video compression using adaptive particle swarm optimization
URI	https://link.springer.com/article/10.1007/s00521-019-04635-6 https://www.proquest.com/docview/2424564612 https://www.proquest.com/docview/3218547386
Volume	32
WOSCitedRecordID	wos000500866600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1433-3058 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0004685 issn: 0941-0643 databaseCode: P5Z dateStart: 20120101 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1433-3058 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0004685 issn: 0941-0643 databaseCode: BENPR dateStart: 20120101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1433-3058 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0004685 issn: 0941-0643 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV07T8MwED5By8BCeYpHqTywQUQaO7EzIUAgBqgqHlXFEjmOg5BoWpoCfx-f61BAwMKSwbHlKHe-h-_xAexlKstozLgXhdQ3DoqOvTgNjDBMYxWkXLDcYhH0LnmnI_r9uOsu3EqXVlnJRCuos6HCO_LDwIbomFHIR6NnD1GjMLrqIDTmoY6dylgN6idnne71p8pIC8ppfBjM72HUlc3Y4jm8EUVXGoMDRu160VfVNLM3v4VIreY5b_z3m5dhydmc5HjKJCswp4tVaFR4DsQd7zVQVxbSh5T6YeBKkgoP1VxGypfxq0aAIjORYOnekGAy-jSJtiCYPf9AZCZHKD3JyPEjKd_keECGZnTg6j3X4e787Pb0wnMgDJ6ijE_MKZKBkG3h5740_mwU-UKFlNNchIrFWkkci4LUp1zTPJRScO5nRkqogKeapXQDasWw0JtA4ijWaUQZ07kwdksomZRa8qwd8jwMcn8L2tX_T5TrUI5AGU_JR29lS7PE0CyxNEuiLdj_WDOa9uf4c3azIlTizmqZzKj042tqjCAEaBZm9UHFCbPXv2-2_fdmO7AYoO9ukwmbUJuMX_QuLKjXyWM5bjlGbsF8N7w3z-ub3jsf2vrv
linkProvider	ProQuest
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LT9wwEB5RWqlcSl-IZ_GhPdGoWduJnUNVVbQIxLLiAAhxCY7jICQ2u2wWUP8Uv7EzXodtUcuNA9fYjpX4mxmPZ8YfwMfSlqXIpIrSRMTooLgsygqOyrDILC-UlpXnIjjqql5PHx9n-zNw29bCUFplqxO9oi4Hls7Iv3AfopNokL8NLyNijaLoakuhMYHFrvt1gy5b83XnB67vJ863fh5sbkeBVSCyQqoxwsJwbTo6rmKDDlqaxtomQolKJ1Zmzhp6lvIiFsqJKjFGKxWXCHvLVeFkIfC9z-C5lOgsofzsJyd_1GF6ClD0mCibSIpQpONL9ej8lRx3CkWgkY_Svw3hdHd7LyDr7dzW_FP7Q6_hVdhRs-8TEXgDM65-C_MtWwULyusd2D1PWMQad9YPBVd1REa8ZM3V6NoR_RJ2ZFSYOGCUaj9JEa4Z1QacMVOaIdkGNgzSxpobM-qzAT7th2rW93D4KJ-6ALP1oHaLwLI0c0UqpHSVxl1ZYqQxzqiyk6gq4VW8BJ12vXMb7l8nGpCL_O7maI-RHDGSe4zk6RJs3I0ZTm4febD3aguMPGiiJp-i4p_NArd4RD-tcfTnFnnT5v9PtvzwZOvwcvtgr5t3d3q7KzDH6ZTCp02uwux4dOXW4IW9Hp83ow9ehBicPjYifwNLvFHL
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3dT8IwEG8UjfFF_Iwoah9808Wxdmv3aFSiEQmJSnhbuq4jJjIIA_z37ZUO0KCJ8bVfW_p1d7373Q-h80QmCQkpcwKfuNpAUaETxp6-DONQejHjNDVcBO0GazZ5pxO2FlD8Jtq9cElOMQ2QpSkbXQ2S9GoGfIPXTDCD4WFfi0wnWEVrFEiDwF5_bi8gIw0pp7ZhIL6HEgubWT7GV9E01ze_uUiN5KmX___P22jLap34erpNdtCKynZRuWB0wPaA7yH5ZEh9cK66PQtKyhwQdAnOx8OJAooi3RADeK-PIRx9GkabYYif72KRiAHcn3hgdyTOP8Swh_u6tGcRn_votX73cnPvWBoGRxLKRvocCY-LGndTV2iLNghcLn3CSMp9SUMlBZQFXuwSpkjqC8EZcxN9T0iPxYrG5ACVsn6mDhEOg1DFAaFUpVxrLr6gQijBkprPUt9L3QqqFSsQSZujHKgy3qNZdmUzi5GexcjMYhRU0MWsz2CaoePX1tViYSN7WvPIM-5fqpW9pdVEq0FA0cx178tinefVP3_s6G_Nz9BG67YeNR6aj8do0wPD3kQaVlFpNByrE7QuJ6O3fHhq9vgnejj5Uw
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Motion+segmentation-based+surveillance+video+compression+using+adaptive+particle+swarm+optimization&rft.jtitle=Neural+computing+%26+applications&rft.au=Sengar%2C+Sandeep+Singh&rft.au=Mukhopadhyay%2C+Susanta&rft.date=2020-08-01&rft.issn=0941-0643&rft.eissn=1433-3058&rft.volume=32&rft.issue=15&rft.spage=11443&rft.epage=11457&rft_id=info:doi/10.1007%2Fs00521-019-04635-6&rft.externalDBID=n%2Fa&rft.externalDocID=10_1007_s00521_019_04635_6
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0941-0643&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0941-0643&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0941-0643&client=summon