{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T12:32:53Z","timestamp":1714393973108},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2019,11,17]],"date-time":"2019-11-17T00:00:00Z","timestamp":1573948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,11,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The technical revolution in the field of video recording using the surveillance videos has increased the amount of the video databases that caused the need for an efficient video management system. This paper proposes a hybrid model using the nearest search algorithm (NSA) and the Levenberg\u2013Marquardt (LM)-based non-linear autoregressive exogenous (NARX) neural network for performing the video object retrieval using the trajectories. Initially, the position of the objects in the video are retrieved using NSA and NARX individually, and they are averaged to determine the position of the object. The positions determined using the hybrid model is compared with the original database, and the trajectories of the objects are retrieved based on the minimum distance, which depends on the weighed query-specific distance. Experiments have been carried out using seven videos taken from the CAVIAR dataset, and the performance of the proposed method is compared with the existing methods. This proposed method found to be better than the existing method with respect to multiple object tracking precision (MOTP), multiple object tracking accuracy (MOTA), average tracking accuracy (ATA), precision, recall and F-measure that results a greater MOTP rate of 0.8796, precision rate of 0.8154, recall rate of 0.8408, the F-measure at a rate of 0.8371, MOTA of 0.8459 and ATA of 0.8324.<\/jats:p>","DOI":"10.1093\/comjnl\/bxz113","type":"journal-article","created":{"date-parts":[[2019,11,14]],"date-time":"2019-11-14T12:10:44Z","timestamp":1573733444000},"page":"1738-1755","source":"Crossref","is-referenced-by-count":4,"title":["Weighed query-specific distance and hybrid NARX neural network for video object retrieval"],"prefix":"10.1093","volume":"63","author":[{"given":"C A","family":"Ghuge","sequence":"first","affiliation":[{"name":"Research Scholar, Department of Computer Science and Engineering, KoneruLakshmaiah Education Foundation, Vaddeswaram, Guntur district, AP, India"}]},{"given":"V","family":"Chandra Prakash","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, KoneruLakshmaiah Education Foundation, Vaddeswaram, Guntur district, AP, India"}]},{"given":"Sachin D","family":"Ruikar","sequence":"additional","affiliation":[{"name":"Department of Electronics Engineering, Walchand College of Engineering, Sangli, MH, India"}]}],"member":"286","published-online":{"date-parts":[[2019,11,17]]},"reference":[{"key":"2020120619204125900_ref1","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1109\/TCSVT.2014.2358022","article-title":"Video object retrieval by trajectory and appearance","volume":"25","author":"Lai","year":"2015","journal-title":"IEEE Trans. Circ. Syst. Vid. Tech."},{"key":"2020120619204125900_ref2","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1049\/iet-cvi.2015.0291","article-title":"Multiple deep features learning for object retrieval in surveillance videos","volume":"10","author":"Guo","year":"2016","journal-title":"IET Comput. Vis."},{"key":"2020120619204125900_ref3","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1016\/j.patrec.2009.04.003","article-title":"Trajectory representation using Gabor features for motion-based video retrieval","volume":"30","author":"Dyana","year":"2009","journal-title":"Pattern Recognit. Lett."},{"key":"2020120619204125900_ref4","doi-asserted-by":"crossref","first-page":"5905","DOI":"10.1109\/TIP.2016.2616297","article-title":"Spatial pyramid covariance-based compact video code for robust face retrieval in TV-series","volume":"25","author":"Li","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"2020120619204125900_ref5","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1109\/TMM.2015.2391674","article-title":"Pattern-based near-duplicate video retrieval and localization on web-scale videos","volume":"17","author":"Chou","year":"2015","journal-title":"IEEE Trans. Multimedia"},{"key":"2020120619204125900_ref6","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1007\/s11042-006-0029-z","article-title":"Video retrieval of near-duplicates using \u03ba-nearest neighbor retrieval of spatiotemporal descriptors","volume":"30","author":"Menthon","year":"2006","journal-title":"Multimed. Tools Appl."},{"key":"2020120619204125900_ref7","doi-asserted-by":"crossref","first-page":"3565","DOI":"10.1016\/j.neucom.2011.06.025","article-title":"An efficient approach to content-based object retrieval in videos","volume":"74","author":"Hong","year":"2011","journal-title":"Neurocomputing"},{"key":"2020120619204125900_ref8","first-page":"7088","article-title":"Content-based video retrieval by genre recognition using tree pruning technique","volume":"3","author":"Fegade","year":"2014","journal-title":"Int. J. Eng. Comp. Sci."},{"key":"2020120619204125900_ref9","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1007\/s11042-006-0048-9","article-title":"Compressed domain video retrieval using object and global motion descriptors","volume":"32","author":"Babu","year":"2007","journal-title":"Multimed. Tools Appl."},{"key":"2020120619204125900_ref10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TMM.2016.2610324","article-title":"Stochastic multiview hashing for large-scale near-duplicate video retrieval","volume":"19","author":"Hao","year":"2017","journal-title":"IEEE Trans. Multimedia"},{"key":"2020120619204125900_ref11","first-page":"1","article-title":"Evaluation of object based video retrieval using SIFT","volume":"1","author":"Gupta","year":"2011","journal-title":"Int. J. Soft Comput. Eng."},{"key":"2020120619204125900_ref12","article-title":"VRFP: on-the-fly video retrieval using web images and fast fisher vector products","volume":"19","author":"Han","year":"2017","journal-title":"IEEE Tran. Multimedia"},{"issue":"6","key":"2020120619204125900_ref13","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.1109\/TCSVT.2017.2667710","article-title":"Large-scale video retrieval using image queries","volume":"28","author":"Araujo","year":"2017","journal-title":"IEEE Trans. Circ. Syst. Vid. Tech."},{"key":"2020120619204125900_ref14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.imavis.2015.02.003","article-title":"Incremental probabilistic latent semantic analysis for video retrieval","volume":"38","author":"Fernandez-Beltran","year":"2015","journal-title":"Image Vision Comput."},{"key":"2020120619204125900_ref15","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1109\/TCSVT.2008.918458","article-title":"Face-based digital signatures for video retrieval","volume":"18","author":"Cotsaces","year":"2008","journal-title":"IEEE Trans. Circ. Syst. Vid. Tech."},{"key":"2020120619204125900_ref16","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1080\/13682199.2016.1231990","article-title":"Integrating GWTM and BAT algorithm for face recognition in low-resolution images","volume":"64","author":"Thomas","year":"2016","journal-title":"Imaging Sci. J."},{"issue":"5","key":"2020120619204125900_ref17","doi-asserted-by":"crossref","first-page":"6521","DOI":"10.1007\/s11042-016-3307-4","article-title":"SurvSurf: human retrieval on large surveillance video data","volume":"76","author":"Ding","year":"2017","journal-title":"Multimed. Tools Appl."},{"issue":"16","key":"2020120619204125900_ref18","doi-asserted-by":"crossref","first-page":"17129","DOI":"10.1007\/s11042-016-3640-7","article-title":"A retrieval algorithm for specific face images in airport surveillance multimedia videos on cloud computing platform","volume":"76","author":"Zhang","year":"2017","journal-title":"Multimed. Tools Appl."},{"key":"2020120619204125900_ref19","doi-asserted-by":"crossref","first-page":"2313","DOI":"10.1109\/TCSVT.2015.2473295","article-title":"Retrieval in long-surveillance videos using user-described motion and object attributes","volume":"26","author":"Casta\u00f1\u00f3n","year":"2016","journal-title":"IEEE Trans. Circ. Syst. Vid. Tech."},{"key":"2020120619204125900_ref20","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1109\/TCSVT.2010.2051367","article-title":"MST-CSS (multi-spectro-temporal curvature scale space), a novel spatio-temporal representation for content-based video retrieval","volume":"20","author":"Dyana","year":"2010","journal-title":"IEEE Trans. Circ. Syst. Vid. Tech."},{"key":"2020120619204125900_ref21","doi-asserted-by":"crossref","first-page":"2861","DOI":"10.1007\/s11042-013-1750-z","article-title":"Quick browsing and retrieval for surveillance videos","volume":"74","author":"Chiang","year":"2015","journal-title":"Multimed. Tools Appl."},{"key":"2020120619204125900_ref22","doi-asserted-by":"crossref","first-page":"6373","DOI":"10.1007\/s11042-015-2576-7","article-title":"Smart video summarization using mealy machine-based trajectory modeling for surveillance applications","volume":"75","author":"Dogra","year":"2016","journal-title":"Multimed. Tools Appl."},{"key":"2020120619204125900_ref23","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1007\/s11042-010-0602-3","article-title":"Spatio-temporal tube data representation and kernel design for SVM-based video object retrieval system","volume":"55","author":"Zhao","year":"2011","journal-title":"Multimed. Tools Appl."},{"key":"2020120619204125900_ref24","first-page":"450","article-title":"Scalable object-based video retrieval in HD video databases","volume":"25","author":"Morand","year":"2010","journal-title":"Image Commun."},{"key":"2020120619204125900_ref25","first-page":"1","article-title":"Trajectory matching and classification of video moving objects","author":"Zheng","year":"2005","journal-title":"IEEE 7th Workshop on Multimedia Signal Processing"},{"key":"2020120619204125900_ref26","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1109\/TCSVT.2006.869965","article-title":"Motion-based video retrieval by trajectory matching","volume":"16","author":"Hsieh","year":"2006","journal-title":"IEEE Trans. Circ. Syst. Vid. Tech."},{"key":"2020120619204125900_ref27","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1109\/TMM.2008.917339","article-title":"Batch nearest neighbor search for video retrieval","volume":"10","author":"Shao","year":"2008","journal-title":"IEEE Trans. Multimedia"},{"key":"2020120619204125900_ref28","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1515\/jisys-2016-0106","article-title":"Query-specific distance and hybrid tracking model for video object retrieval","volume":"27","author":"Ghuge","year":"2016","journal-title":"J. Intell. Syst."},{"key":"2020120619204125900_ref29","author":"CAVIAR Test Case Scenarios, Available at"}],"container-title":["The Computer Journal"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/comjnl\/article-pdf\/63\/11\/1738\/34315108\/bxz113.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/comjnl\/article-pdf\/63\/11\/1738\/34315108\/bxz113.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,7]],"date-time":"2020-12-07T02:29:43Z","timestamp":1607308183000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/comjnl\/article\/63\/11\/1738\/5618962"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,17]]},"references-count":29,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2019,11,17]]},"published-print":{"date-parts":[[2020,11,19]]}},"URL":"https:\/\/doi.org\/10.1093\/comjnl\/bxz113","relation":{},"ISSN":["0010-4620","1460-2067"],"issn-type":[{"value":"0010-4620","type":"print"},{"value":"1460-2067","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,11]]},"published":{"date-parts":[[2019,11,17]]}}}