Motion detection using block based bi-directional optical flow method
[Display omitted] •Optical flow based moving object detection algorithm is proposed.•Bi-directional optical flow field is used for motion estimation and detection.•A histogram and plot based thresholding scheme is employed for motion detection.•Foreground is detected using morphological operation, c...
Saved in:
| Published in: | Journal of visual communication and image representation Vol. 49; pp. 89 - 103 |
|---|---|
| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Inc
01.11.2017
|
| Subjects: | |
| ISSN: | 1047-3203, 1095-9076 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | [Display omitted]
•Optical flow based moving object detection algorithm is proposed.•Bi-directional optical flow field is used for motion estimation and detection.•A histogram and plot based thresholding scheme is employed for motion detection.•Foreground is detected using morphological operation, connected component analysis.•Our technique is compared with existing methods using real video datasets.
Detecting moving objects from video frame sequences has a lot of useful applications in computer vision. This proposed method of moving object detection first estimates the bi-directional optical flow fields between (i) the current frame and the previous frame and between (ii) the current frame and the next frame. The bi-directional optical flow field is then subjected to normalization and enhancement. Each normalized and enhanced optical flow field is then divided into non-overlapping blocks. The moving objects are finally detected in the form of binary blobs by examining the histogram based thresholded values of such optical flow field of each block as well as the optical flow field of the candidate flow value. Our technique has been conceptualized, implemented and tested on real video data sets with complex background environment. The experimental results and quantitative evaluation establish that our technique achieves effective and efficient results than other existing methods. |
|---|---|
| AbstractList | [Display omitted]
•Optical flow based moving object detection algorithm is proposed.•Bi-directional optical flow field is used for motion estimation and detection.•A histogram and plot based thresholding scheme is employed for motion detection.•Foreground is detected using morphological operation, connected component analysis.•Our technique is compared with existing methods using real video datasets.
Detecting moving objects from video frame sequences has a lot of useful applications in computer vision. This proposed method of moving object detection first estimates the bi-directional optical flow fields between (i) the current frame and the previous frame and between (ii) the current frame and the next frame. The bi-directional optical flow field is then subjected to normalization and enhancement. Each normalized and enhanced optical flow field is then divided into non-overlapping blocks. The moving objects are finally detected in the form of binary blobs by examining the histogram based thresholded values of such optical flow field of each block as well as the optical flow field of the candidate flow value. Our technique has been conceptualized, implemented and tested on real video data sets with complex background environment. The experimental results and quantitative evaluation establish that our technique achieves effective and efficient results than other existing methods. |
| Author | Mukhopadhyay, Susanta Sengar, Sandeep Singh |
| Author_xml | – sequence: 1 givenname: Sandeep Singh surname: Sengar fullname: Sengar, Sandeep Singh email: sandeep.iitdhanbad@gmail.com – sequence: 2 givenname: Susanta surname: Mukhopadhyay fullname: Mukhopadhyay, Susanta |
| BookMark | eNqFkL1OwzAUhS1UJNrCE7DkBRKu4zSOBwZUlR-piAVmy7GvwSGNKzsU8fYkDRMDTOdIV9-Vzrcgs853SMglhYwCLa-arDloF7IcKM-gygD4CZlTEKtUAC9nYy94ynJgZ2QRYwMATLBiTjaPvne-Swz2qI_tI7ruNalbr9-TWkU0Se1S48J0Vm3i973TQ9rWfyY77N-8OSenVrURL35ySV5uN8_r-3T7dPewvtmmmgHr08KgWKlcMFaVqJQtrFI50srWohC1rsBWRgmBuS0LrpFTwzmtyhqKUlCrGFsSNv3VwccY0Mp9cDsVviQFOZqQjTyakKMJCZUcTAyU-EVp16txTR-Ua_9hrycWh1kHh0FG7bDTOBmRxrs_-W-vrX51 |
| CitedBy_id | crossref_primary_10_1016_j_measurement_2024_114336 crossref_primary_10_1007_s00138_020_01126_w crossref_primary_10_1109_TITS_2024_3418949 crossref_primary_10_1007_s12204_020_2219_7 crossref_primary_10_1016_j_knosys_2022_109612 crossref_primary_10_1371_journal_pone_0308933 crossref_primary_10_1109_TCSVT_2020_3023175 crossref_primary_10_1007_s11042_019_08506_z crossref_primary_10_1080_1206212X_2020_1758877 crossref_primary_10_1007_s10514_020_09964_3 crossref_primary_10_1016_j_displa_2023_102454 crossref_primary_10_1177_03611981231159128 crossref_primary_10_1016_j_aei_2020_101100 crossref_primary_10_1016_j_jvcir_2022_103686 crossref_primary_10_1007_s00521_019_04635_6 crossref_primary_10_1007_s11042_023_16556_7 crossref_primary_10_3390_rs15020417 |
| Cites_doi | 10.1109/TITS.2009.2030963 10.1016/j.imavis.2011.12.001 10.1016/0004-3702(81)90024-2 10.1016/j.robot.2010.06.002 10.1109/TAES.1976.308294 10.1007/s00521-013-1393-z 10.1016/j.jvcir.2015.03.003 10.1016/j.dsp.2012.07.017 10.1016/j.trit.2016.03.005 10.1016/j.jvcir.2016.10.016 10.1016/j.ijleo.2014.06.092 10.1109/TCSVT.2014.2335852 10.1016/j.patrec.2005.03.031 10.1109/34.868684 10.1109/34.868683 10.1016/j.imavis.2006.01.021 10.1016/j.compeleceng.2014.10.003 10.1109/TIE.2012.2206330 10.1016/j.ijleo.2016.03.061 10.1016/j.jvcir.2015.04.011 10.1016/j.cosrev.2014.04.001 10.1109/LSP.2014.2310494 10.1007/s13369-017-2672-2 10.1016/j.ijleo.2017.07.040 10.1016/j.measurement.2015.07.020 |
| ContentType | Journal Article |
| Copyright | 2017 Elsevier Inc. |
| Copyright_xml | – notice: 2017 Elsevier Inc. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.jvcir.2017.08.007 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Journalism & Communications Engineering |
| EISSN | 1095-9076 |
| EndPage | 103 |
| ExternalDocumentID | 10_1016_j_jvcir_2017_08_007 S1047320317301700 |
| GroupedDBID | --K --M .DC .~1 0R~ 1B1 1~. 1~5 29L 4.4 457 4G. 53G 5GY 5VS 7-5 71M 8P~ 9JN AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO AAYFN ABBOA ABFNM ABJNI ABMAC ABXDB ABYKQ ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADFGL ADJOM ADMHC ADMUD ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CAG COF CS3 DM4 DU5 EBS EFBJH EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA GBOLZ HLZ HVGLF HZ~ IHE J1W JJJVA KOM LG5 LX9 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SBC SDF SDG SDP SES SEW SPC SPCBC SST SSV SSZ T5K WH7 WUQ XPP YQT ZMT ZU3 ~G- 9DU AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c303t-4de95a293386eaaf4faa2e18fb949bc80f8da99e2f647ce71d77186b04691fa33 |
| ISICitedReferencesCount | 20 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000416613800008&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1047-3203 |
| IngestDate | Sat Nov 29 04:56:35 EST 2025 Tue Nov 18 22:05:00 EST 2025 Fri Feb 23 02:24:21 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Block Motion detection Normalization Morphology Optical flow |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c303t-4de95a293386eaaf4faa2e18fb949bc80f8da99e2f647ce71d77186b04691fa33 |
| PageCount | 15 |
| ParticipantIDs | crossref_primary_10_1016_j_jvcir_2017_08_007 crossref_citationtrail_10_1016_j_jvcir_2017_08_007 elsevier_sciencedirect_doi_10_1016_j_jvcir_2017_08_007 |
| PublicationCentury | 2000 |
| PublicationDate | November 2017 2017-11-00 |
| PublicationDateYYYYMMDD | 2017-11-01 |
| PublicationDate_xml | – month: 11 year: 2017 text: November 2017 |
| PublicationDecade | 2010 |
| PublicationTitle | Journal of visual communication and image representation |
| PublicationYear | 2017 |
| Publisher | Elsevier Inc |
| Publisher_xml | – name: Elsevier Inc |
| References | Horn, Schunck (b0145) 1981; 17 Megrhi, Jmal, Souidene, Beghdadi (b0025) 2016; 41 D.K. Prasad, D. Rajan, L. Rachmawati, E. Rajabaly, C. Quek, Video processing from electro-optical sensors for object detection and tracking in maritime environment: a survey, 2016, pp. 1–23. Available from: arXiv:1611.05842. Database: Images & Video Clips (2), Collected by The HDTV Group, July, 2006. Yan, Zhang, Xu, Dai, Zhang, Dai, Wu (b0135) 2014; 24 Stauffer, Grimson (b0115) 1999 Dougherty, Lotufo (b0205) 2003; Vol. 71 Sengar, Mukhopadhyay (b0220) 2017 Sengar, Mukhopadhyay (b0125) 2017; 42 Garcia, Gardel, Bravo, Lazaro, Martinez, Rodriguez (b0020) 2013; 60 Bouguet (b0080) 2001; 5 Yan, Zhang, Xu, Dai, Li, Dai, Wu (b0140) 2014; 21 Foresti, Micheloni, Piciarelli (b0065) 2005; 26 J.V.D. Vyver, Detection of Moving Objects in the HEVC Compressed Domain for Ultra-High Resolution Video, Master’s thesis, Ghent University, June 2016. Sengar, Mukhopadhyay (b0005) 2016 Halidou, You, Hamidine, Etoundi, Diakite (b0070) 2014; 40 Sengar, Mukhopadhyay (b0040) 2016 Sengar, Mukhopadhyay (b0050) 2017 Bouwmans (b0045) 2014; 11 Deng, Cahill (b0195) 1993; vol. 3 Oliver, Rosario, Pentland (b0110) 2000; 22 Haritaoglu, Harwood, Davis (b0120) 2000; 22 Motlagh, Nakhaeinia, Tang, Karasfi, Khaksar (b0015) 2014; 24 Maddalena, Petrosino (b0105) 2012 Caviar Test Case Scenarios, dataset, Dec, 2011. vidme, videodata, July, 2015. Foy (b0200) 1976; 12 Zhao, Xia, Xu, Shi, Liu (b0010) 2016; 37 Tagliasacchi (b0170) 2007; 25 Liao, Chen, Chung (b0185) 2001; 17 Xin, Hou, Dong, Ding (b0190) 2014; 125 R.T. Collins, A.J. Lipton, T. Kanade, H. Fujiyoshi, D. Duggins, Y. Tsin, D. Tolliver, N. Enomoto, O. Hasegawa, P. Burt, L. Wixson, A system for video surveillance and monitoring, Tech. Rep. CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University, May 2000. . Liu, Yu (b0180) 2009 Paul, Singh, Midya, Roy, Dogra (b0085) 2016 Schwarz, Mkhitaryan, Mateus, Navab (b0155) 2012; 30 Caballero, Castillo, Cantos, Tomas (b0075) 2010; 58 Choi, Pak, Ahn, Lee, Lim, Song (b0160) 2015; 75 Bouwmans (b0095) 2012 Sengar, Mukhopadhyay (b0175) 2016; 127 Hu, Chen, Chen, Huang, Wu (b0090) 2015; 30 Chen, Xu, Yang, Zhang (b0150) 2013; 23 Xu, Dong, Zhang, Xu (b0100) 2016; 1 Kim, Ye, Kim (b0165) 2010 Bouwmans, Sobral, Javed, Jung, Zahzah (b0060) 2016 Candamo, Shreve, Goldgof, Sapper, Kasturi (b0030) 2010; 11 Zhao (10.1016/j.jvcir.2017.08.007_b0010) 2016; 37 Sengar (10.1016/j.jvcir.2017.08.007_b0125) 2017; 42 Sengar (10.1016/j.jvcir.2017.08.007_b0220) 2017 Megrhi (10.1016/j.jvcir.2017.08.007_b0025) 2016; 41 Bouwmans (10.1016/j.jvcir.2017.08.007_b0045) 2014; 11 Stauffer (10.1016/j.jvcir.2017.08.007_b0115) 1999 Xin (10.1016/j.jvcir.2017.08.007_b0190) 2014; 125 Halidou (10.1016/j.jvcir.2017.08.007_b0070) 2014; 40 Chen (10.1016/j.jvcir.2017.08.007_b0150) 2013; 23 10.1016/j.jvcir.2017.08.007_b0225 Kim (10.1016/j.jvcir.2017.08.007_b0165) 2010 Sengar (10.1016/j.jvcir.2017.08.007_b0175) 2016; 127 Horn (10.1016/j.jvcir.2017.08.007_b0145) 1981; 17 Xu (10.1016/j.jvcir.2017.08.007_b0100) 2016; 1 Hu (10.1016/j.jvcir.2017.08.007_b0090) 2015; 30 Motlagh (10.1016/j.jvcir.2017.08.007_b0015) 2014; 24 Dougherty (10.1016/j.jvcir.2017.08.007_b0205) 2003; Vol. 71 Choi (10.1016/j.jvcir.2017.08.007_b0160) 2015; 75 Bouguet (10.1016/j.jvcir.2017.08.007_b0080) 2001; 5 Paul (10.1016/j.jvcir.2017.08.007_b0085) 2016 Maddalena (10.1016/j.jvcir.2017.08.007_b0105) 2012 Schwarz (10.1016/j.jvcir.2017.08.007_b0155) 2012; 30 10.1016/j.jvcir.2017.08.007_b0130 Foresti (10.1016/j.jvcir.2017.08.007_b0065) 2005; 26 Liu (10.1016/j.jvcir.2017.08.007_b0180) 2009 Garcia (10.1016/j.jvcir.2017.08.007_b0020) 2013; 60 Bouwmans (10.1016/j.jvcir.2017.08.007_b0095) 2012 Yan (10.1016/j.jvcir.2017.08.007_b0135) 2014; 24 Deng (10.1016/j.jvcir.2017.08.007_b0195) 1993; vol. 3 Oliver (10.1016/j.jvcir.2017.08.007_b0110) 2000; 22 10.1016/j.jvcir.2017.08.007_b0215 Haritaoglu (10.1016/j.jvcir.2017.08.007_b0120) 2000; 22 10.1016/j.jvcir.2017.08.007_b0055 Yan (10.1016/j.jvcir.2017.08.007_b0140) 2014; 21 Bouwmans (10.1016/j.jvcir.2017.08.007_b0060) 2016 Liao (10.1016/j.jvcir.2017.08.007_b0185) 2001; 17 10.1016/j.jvcir.2017.08.007_b0210 10.1016/j.jvcir.2017.08.007_b0035 Sengar (10.1016/j.jvcir.2017.08.007_b0040) 2016 Caballero (10.1016/j.jvcir.2017.08.007_b0075) 2010; 58 Candamo (10.1016/j.jvcir.2017.08.007_b0030) 2010; 11 Tagliasacchi (10.1016/j.jvcir.2017.08.007_b0170) 2007; 25 Foy (10.1016/j.jvcir.2017.08.007_b0200) 1976; 12 Sengar (10.1016/j.jvcir.2017.08.007_b0005) 2016 Sengar (10.1016/j.jvcir.2017.08.007_b0050) 2017 |
| References_xml | – volume: 21 start-page: 573 year: 2014 end-page: 576 ident: b0140 article-title: A highly parallel framework for HEVC coding unit partitioning tree decision on many-core processors publication-title: IEEE Signal Process. Lett. – start-page: 21 year: 2012 end-page: 26 ident: b0105 article-title: The SOBS algorithm: what are the limits? publication-title: Workshop on Computer Vision and Pattern Recognition – reference: vidme, videodata, July, 2015. < – start-page: 4669 year: 2010 end-page: 4672 ident: b0165 article-title: Moving object detection under free-moving camera publication-title: 17th IEEE International Conference on Image Processing – volume: 41 start-page: 375 year: 2016 end-page: 390 ident: b0025 article-title: Spatio-temporal action localization and detection for human action recognition in big dataset publication-title: J. Vis. Commun. Image Represent. – volume: 11 start-page: 206 year: 2010 end-page: 224 ident: b0030 article-title: Understanding transit scenes: a survey on human behavior-recognition algorithms publication-title: IEEE Trans. Intell. Transport. Syst. – volume: vol. 3 start-page: 1615 year: 1993 end-page: 1619 ident: b0195 article-title: An adaptive gaussian filter for noise reduction and edge detection publication-title: Nuclear Science Symposium and Medical Imaging – volume: 37 start-page: 25 year: 2016 end-page: 31 ident: b0010 article-title: APPOS: an adaptive partial occlusion segmentation method for multiple vehicles tracking publication-title: J. Vis. Commun. Image Represent. – volume: 58 start-page: 1273 year: 2010 end-page: 1281 ident: b0075 article-title: Optical flow or image subtraction in human detection from infrared camera on mobile robot publication-title: J. Robot. Auton. Syst. – start-page: 103 year: 2012 end-page: 138 ident: b0095 article-title: Background subtraction for visual surveillance: a fuzzy approach publication-title: Handbook on Soft Computing for Video Surveillance – volume: 75 start-page: 338 year: 2015 end-page: 353 ident: b0160 article-title: Arbitration algorithm of FIR filter and optical flow based on ANFIS for visual object tracking publication-title: J. Meas. – reference: J.V.D. Vyver, Detection of Moving Objects in the HEVC Compressed Domain for Ultra-High Resolution Video, Master’s thesis, Ghent University, June 2016. – volume: 12 start-page: 187 year: 1976 end-page: 194 ident: b0200 article-title: Position-location solutions by Taylor-series estimation publication-title: IEEE Trans. Aerospace Electron. Syst. – volume: 40 start-page: 375 year: 2014 end-page: 389 ident: b0070 article-title: Fast pedestrian detection based on region of interest and multi-block local binary pattern descriptors publication-title: Comput. Electr. Eng. – volume: 23 start-page: 118 year: 2013 end-page: 125 ident: b0150 article-title: Quaternion based optical flow estimation for robust object tracking publication-title: J. Digit. Signal Process. – volume: 127 start-page: 6258 year: 2016 end-page: 6267 ident: b0175 article-title: Moving object area detection using normalized self adaptive optical flow publication-title: Optik-Int. J. Light Electron Opt. – volume: 25 start-page: 141 year: 2007 end-page: 147 ident: b0170 article-title: A genetic algorithm for optical flow estimation publication-title: J. Image Vis. Comput. – volume: Vol. 71 year: 2003 ident: b0205 publication-title: Hands-on Morphological Image Processing – reference: Caviar Test Case Scenarios, dataset, Dec, 2011. < – volume: 125 start-page: 5690 year: 2014 end-page: 5694 ident: b0190 article-title: A self-adaptive optical flow method for the moving object detection in the video sequences publication-title: Int. J. Light Electron Opt. – volume: 17 start-page: 713 year: 2001 end-page: 727 ident: b0185 article-title: A fast algorithm for multilevel thresholding publication-title: J. Inform. Sci. Eng. – start-page: 1 year: 2017 end-page: 8 ident: b0220 article-title: Moving object detection based on frame difference and w4 publication-title: Signal Image Video Process. – volume: 26 start-page: 2232 year: 2005 end-page: 2243 ident: b0065 article-title: Detecting moving people in video streams publication-title: Pattern Recogn. Lett. – volume: 22 start-page: 831 year: 2000 end-page: 843 ident: b0110 article-title: Bayesian computer vision system for modeling human interactions publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 60 start-page: 3991 year: 2013 end-page: 4000 ident: b0020 article-title: Directional people counter based on head tracking publication-title: IEEE Trans. Ind. Electron. – year: 2017 ident: b0050 article-title: Detection of moving objects based on enhancement of optical flow publication-title: Optik-Int. J. Light Electron Opt. – reference: >. – reference: D.K. Prasad, D. Rajan, L. Rachmawati, E. Rajabaly, C. Quek, Video processing from electro-optical sensors for object detection and tracking in maritime environment: a survey, 2016, pp. 1–23. Available from: arXiv:1611.05842. – volume: 1 start-page: 43 year: 2016 end-page: 60 ident: b0100 article-title: Background modeling methods in video analysis: a review and comparative evaluation publication-title: CAAI Trans. Intell. Technol. – volume: 24 start-page: 1569 year: 2014 end-page: 1581 ident: b0015 article-title: Automatic navigation of mobile robots in unknown environments publication-title: J. Neural Comput. Appl. – volume: 17 start-page: 185 year: 1981 end-page: 203 ident: b0145 article-title: Determining optical flow publication-title: J. Artif. Intell. – volume: 42 start-page: 3621 year: 2017 end-page: 3633 ident: b0125 article-title: Foreground detection via background subtraction and improved three-frame differencing publication-title: Arab. J. Sci. Eng. – volume: 11 start-page: 31 year: 2014 end-page: 66 ident: b0045 article-title: Traditional and recent approaches in background modeling for foreground detection: An overview publication-title: Comput. Sci. Rev. – start-page: 1 year: 2016 end-page: 20 ident: b0085 article-title: Moving object detection using modified temporal differencing and local fuzzy thresholding publication-title: J. Supercomput. – volume: 24 start-page: 2077 year: 2014 end-page: 2089 ident: b0135 article-title: Efficient parallel framework for HEVC motion estimation on many-core processors publication-title: IEEE Trans. Circ. Syst. Video Technol. – volume: 30 start-page: 217 year: 2012 end-page: 226 ident: b0155 article-title: Human skeleton tracking from depth data using geodesic distances and optical flow publication-title: J. Image Vis. Comput. – reference: R.T. Collins, A.J. Lipton, T. Kanade, H. Fujiyoshi, D. Duggins, Y. Tsin, D. Tolliver, N. Enomoto, O. Hasegawa, P. Burt, L. Wixson, A system for video surveillance and monitoring, Tech. Rep. CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University, May 2000. – volume: 22 start-page: 809 year: 2000 end-page: 830 ident: b0120 article-title: : real-time surveillance of people and their activities publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – start-page: 344 year: 2009 end-page: 349 ident: b0180 article-title: Otsu method and k-means publication-title: 9th International Conference on Hybrid Intelligent Systems – year: 2016 ident: b0060 article-title: Decomposition into low-rank plus additive matrices for background/foreground separation: a review for a comparative evaluation with a large-scale dataset publication-title: Comput. Sci. Rev. – start-page: 2345 year: 2016 end-page: 2349 ident: b0005 article-title: Moving object tracking using Laplacian-DCT based perceptual hash publication-title: International Conference on Wireless Communications, Signal Processing and Networking – volume: 30 start-page: 164 year: 2015 end-page: 180 ident: b0090 article-title: Moving object detection and tracking from video captured by moving camera publication-title: J. Vis. Commun. Image Represent. – start-page: 467 year: 2016 end-page: 472 ident: b0040 article-title: A novel method for moving object detection based on block based frame differencing publication-title: 2016 3rd International Conference on Recent Advances in Information Technology (RAIT) – volume: 5 start-page: 1 year: 2001 end-page: 10 ident: b0080 article-title: Pyramidal implementation of the affine Lucas kanade feature tracker description of the algorithm publication-title: Intel Corpor. – year: 1999 ident: b0115 article-title: Adaptive background mixture models for real-time tracking publication-title: International Conference On Computer Vision and Pattern Recognition – reference: Database: Images & Video Clips (2), Collected by The HDTV Group, July, 2006. < – volume: 11 start-page: 206 year: 2010 ident: 10.1016/j.jvcir.2017.08.007_b0030 article-title: Understanding transit scenes: a survey on human behavior-recognition algorithms publication-title: IEEE Trans. Intell. Transport. Syst. doi: 10.1109/TITS.2009.2030963 – start-page: 21 year: 2012 ident: 10.1016/j.jvcir.2017.08.007_b0105 article-title: The SOBS algorithm: what are the limits? – volume: 30 start-page: 217 year: 2012 ident: 10.1016/j.jvcir.2017.08.007_b0155 article-title: Human skeleton tracking from depth data using geodesic distances and optical flow publication-title: J. Image Vis. Comput. doi: 10.1016/j.imavis.2011.12.001 – start-page: 2345 year: 2016 ident: 10.1016/j.jvcir.2017.08.007_b0005 article-title: Moving object tracking using Laplacian-DCT based perceptual hash – volume: 17 start-page: 185 year: 1981 ident: 10.1016/j.jvcir.2017.08.007_b0145 article-title: Determining optical flow publication-title: J. Artif. Intell. doi: 10.1016/0004-3702(81)90024-2 – volume: 58 start-page: 1273 year: 2010 ident: 10.1016/j.jvcir.2017.08.007_b0075 article-title: Optical flow or image subtraction in human detection from infrared camera on mobile robot publication-title: J. Robot. Auton. Syst. doi: 10.1016/j.robot.2010.06.002 – volume: 12 start-page: 187 year: 1976 ident: 10.1016/j.jvcir.2017.08.007_b0200 article-title: Position-location solutions by Taylor-series estimation publication-title: IEEE Trans. Aerospace Electron. Syst. doi: 10.1109/TAES.1976.308294 – start-page: 1 year: 2017 ident: 10.1016/j.jvcir.2017.08.007_b0220 article-title: Moving object detection based on frame difference and w4 publication-title: Signal Image Video Process. – volume: 24 start-page: 1569 year: 2014 ident: 10.1016/j.jvcir.2017.08.007_b0015 article-title: Automatic navigation of mobile robots in unknown environments publication-title: J. Neural Comput. Appl. doi: 10.1007/s00521-013-1393-z – year: 2016 ident: 10.1016/j.jvcir.2017.08.007_b0060 article-title: Decomposition into low-rank plus additive matrices for background/foreground separation: a review for a comparative evaluation with a large-scale dataset publication-title: Comput. Sci. Rev. – volume: 30 start-page: 164 year: 2015 ident: 10.1016/j.jvcir.2017.08.007_b0090 article-title: Moving object detection and tracking from video captured by moving camera publication-title: J. Vis. Commun. Image Represent. doi: 10.1016/j.jvcir.2015.03.003 – volume: 23 start-page: 118 year: 2013 ident: 10.1016/j.jvcir.2017.08.007_b0150 article-title: Quaternion based optical flow estimation for robust object tracking publication-title: J. Digit. Signal Process. doi: 10.1016/j.dsp.2012.07.017 – volume: 17 start-page: 713 year: 2001 ident: 10.1016/j.jvcir.2017.08.007_b0185 article-title: A fast algorithm for multilevel thresholding publication-title: J. Inform. Sci. Eng. – volume: 1 start-page: 43 issue: 1 year: 2016 ident: 10.1016/j.jvcir.2017.08.007_b0100 article-title: Background modeling methods in video analysis: a review and comparative evaluation publication-title: CAAI Trans. Intell. Technol. doi: 10.1016/j.trit.2016.03.005 – start-page: 1 year: 2016 ident: 10.1016/j.jvcir.2017.08.007_b0085 article-title: Moving object detection using modified temporal differencing and local fuzzy thresholding publication-title: J. Supercomput. – start-page: 344 year: 2009 ident: 10.1016/j.jvcir.2017.08.007_b0180 article-title: Otsu method and k-means – ident: 10.1016/j.jvcir.2017.08.007_b0225 – start-page: 103 year: 2012 ident: 10.1016/j.jvcir.2017.08.007_b0095 article-title: Background subtraction for visual surveillance: a fuzzy approach – year: 1999 ident: 10.1016/j.jvcir.2017.08.007_b0115 article-title: Adaptive background mixture models for real-time tracking – volume: 41 start-page: 375 year: 2016 ident: 10.1016/j.jvcir.2017.08.007_b0025 article-title: Spatio-temporal action localization and detection for human action recognition in big dataset publication-title: J. Vis. Commun. Image Represent. doi: 10.1016/j.jvcir.2016.10.016 – volume: 125 start-page: 5690 issue: 19 year: 2014 ident: 10.1016/j.jvcir.2017.08.007_b0190 article-title: A self-adaptive optical flow method for the moving object detection in the video sequences publication-title: Int. J. Light Electron Opt. doi: 10.1016/j.ijleo.2014.06.092 – volume: 5 start-page: 1 year: 2001 ident: 10.1016/j.jvcir.2017.08.007_b0080 article-title: Pyramidal implementation of the affine Lucas kanade feature tracker description of the algorithm publication-title: Intel Corpor. – ident: 10.1016/j.jvcir.2017.08.007_b0055 – volume: vol. 3 start-page: 1615 year: 1993 ident: 10.1016/j.jvcir.2017.08.007_b0195 article-title: An adaptive gaussian filter for noise reduction and edge detection – volume: 24 start-page: 2077 year: 2014 ident: 10.1016/j.jvcir.2017.08.007_b0135 article-title: Efficient parallel framework for HEVC motion estimation on many-core processors publication-title: IEEE Trans. Circ. Syst. Video Technol. doi: 10.1109/TCSVT.2014.2335852 – volume: 26 start-page: 2232 issue: 14 year: 2005 ident: 10.1016/j.jvcir.2017.08.007_b0065 article-title: Detecting moving people in video streams publication-title: Pattern Recogn. Lett. doi: 10.1016/j.patrec.2005.03.031 – start-page: 4669 year: 2010 ident: 10.1016/j.jvcir.2017.08.007_b0165 article-title: Moving object detection under free-moving camera – volume: 22 start-page: 831 year: 2000 ident: 10.1016/j.jvcir.2017.08.007_b0110 article-title: Bayesian computer vision system for modeling human interactions publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.868684 – volume: 22 start-page: 809 issue: 8 year: 2000 ident: 10.1016/j.jvcir.2017.08.007_b0120 article-title: W4: real-time surveillance of people and their activities publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.868683 – volume: 25 start-page: 141 year: 2007 ident: 10.1016/j.jvcir.2017.08.007_b0170 article-title: A genetic algorithm for optical flow estimation publication-title: J. Image Vis. Comput. doi: 10.1016/j.imavis.2006.01.021 – volume: 40 start-page: 375 issue: 8 year: 2014 ident: 10.1016/j.jvcir.2017.08.007_b0070 article-title: Fast pedestrian detection based on region of interest and multi-block local binary pattern descriptors publication-title: Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2014.10.003 – ident: 10.1016/j.jvcir.2017.08.007_b0210 – start-page: 467 year: 2016 ident: 10.1016/j.jvcir.2017.08.007_b0040 article-title: A novel method for moving object detection based on block based frame differencing – volume: 60 start-page: 3991 year: 2013 ident: 10.1016/j.jvcir.2017.08.007_b0020 article-title: Directional people counter based on head tracking publication-title: IEEE Trans. Ind. Electron. doi: 10.1109/TIE.2012.2206330 – ident: 10.1016/j.jvcir.2017.08.007_b0215 – ident: 10.1016/j.jvcir.2017.08.007_b0130 – volume: 127 start-page: 6258 issue: 16 year: 2016 ident: 10.1016/j.jvcir.2017.08.007_b0175 article-title: Moving object area detection using normalized self adaptive optical flow publication-title: Optik-Int. J. Light Electron Opt. doi: 10.1016/j.ijleo.2016.03.061 – volume: Vol. 71 year: 2003 ident: 10.1016/j.jvcir.2017.08.007_b0205 – volume: 37 start-page: 25 year: 2016 ident: 10.1016/j.jvcir.2017.08.007_b0010 article-title: APPOS: an adaptive partial occlusion segmentation method for multiple vehicles tracking publication-title: J. Vis. Commun. Image Represent. doi: 10.1016/j.jvcir.2015.04.011 – volume: 11 start-page: 31 year: 2014 ident: 10.1016/j.jvcir.2017.08.007_b0045 article-title: Traditional and recent approaches in background modeling for foreground detection: An overview publication-title: Comput. Sci. Rev. doi: 10.1016/j.cosrev.2014.04.001 – volume: 21 start-page: 573 year: 2014 ident: 10.1016/j.jvcir.2017.08.007_b0140 article-title: A highly parallel framework for HEVC coding unit partitioning tree decision on many-core processors publication-title: IEEE Signal Process. Lett. doi: 10.1109/LSP.2014.2310494 – ident: 10.1016/j.jvcir.2017.08.007_b0035 – volume: 42 start-page: 3621 issue: 8 year: 2017 ident: 10.1016/j.jvcir.2017.08.007_b0125 article-title: Foreground detection via background subtraction and improved three-frame differencing publication-title: Arab. J. Sci. Eng. doi: 10.1007/s13369-017-2672-2 – year: 2017 ident: 10.1016/j.jvcir.2017.08.007_b0050 article-title: Detection of moving objects based on enhancement of optical flow publication-title: Optik-Int. J. Light Electron Opt. doi: 10.1016/j.ijleo.2017.07.040 – volume: 75 start-page: 338 year: 2015 ident: 10.1016/j.jvcir.2017.08.007_b0160 article-title: Arbitration algorithm of FIR filter and optical flow based on ANFIS for visual object tracking publication-title: J. Meas. doi: 10.1016/j.measurement.2015.07.020 |
| SSID | ssj0003934 |
| Score | 2.2660353 |
| Snippet | [Display omitted]
•Optical flow based moving object detection algorithm is proposed.•Bi-directional optical flow field is used for motion estimation and... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 89 |
| SubjectTerms | Block Morphology Motion detection Normalization Optical flow |
| Title | Motion detection using block based bi-directional optical flow method |
| URI | https://dx.doi.org/10.1016/j.jvcir.2017.08.007 |
| Volume | 49 |
| WOSCitedRecordID | wos000416613800008&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1095-9076 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0003934 issn: 1047-3203 databaseCode: AIEXJ dateStart: 19950301 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELZQywEOqBQQpQX5gLgsQeu8bB8rtIhWpULaIu0tchybzbbNrprs0v57xo-k2RZW9MAliiLHcTJfZiaTmW8Qei90DH5qmgRCahXELI8DQZQOhlRGIWM6ZdKSuJ7Q01M2mfDv_o9pbdsJ0Kpi19d88V9FDcdA2KZ09gHi7iaFA7APQoctiB22_yT4b7Yvz6BQjXJtwJc2HJCD1TofGKMFLmcZOFPm4oDzhS9kvJj_8i2l_-Kzrsp6aQlFelUl7vfDpcn9sQyZbTVTh7qxqn66NO6xiVirxWAMC5reivp8Cl_uxfRG3HR5Qo3ohyPAxJEuHOE0qKF-iMJh1FexjpXU60jXMshbW-IG3lPkLqYw-zRbydLQthJqmVZdh9x12uw75qxLMmzz12aZnSQzk2Sm56YhH9gOacJBC24fHo0mx53tjrjLQ2hvouWpshmB99byZ1-m55-c7aBnXkj40AHiOXqkql30tEc3uYv2_aCyvsQf8FppUP0CjRxwcAccbIGDLXCwBQ5eBw72wMEGONgB5yX68WV09vlr4JtsBBK8lyaIC8UTAU5fxFIl4NXVQoSKMJ3zmOeSDTUrBOcq1GlMpaKkoODOpLmJqxAtougV2qrmlXqNYH0hKeBzOpExiRU4rqnOKbzzYHAFLRK5h8L2cWXSM9CbRigX2QZR7aGP3UkLR8CyeXjayiHzPqR7Lhkga9OJbx52nX305Bb9B2iruVqqt-ixXDVlffXOw-o3xc-Yrg |
| linkProvider | Elsevier |
| 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+detection+using+block+based+bi-directional+optical+flow+method&rft.jtitle=Journal+of+visual+communication+and+image+representation&rft.au=Sengar%2C+Sandeep+Singh&rft.au=Mukhopadhyay%2C+Susanta&rft.date=2017-11-01&rft.issn=1047-3203&rft.volume=49&rft.spage=89&rft.epage=103&rft_id=info:doi/10.1016%2Fj.jvcir.2017.08.007&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_jvcir_2017_08_007 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1047-3203&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1047-3203&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1047-3203&client=summon |