{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T18:46:38Z","timestamp":1757616398836,"version":"3.44.0"},"reference-count":34,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/lsp.2020.2971387","type":"journal-article","created":{"date-parts":[[2020,2,3]],"date-time":"2020-02-03T15:36:36Z","timestamp":1580744196000},"page":"336-340","source":"Crossref","is-referenced-by-count":2,"title":["Smooth Incremental Learning of Correlation Filters for Visual Tracking"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0032-9116","authenticated-orcid":false,"given":"Jie","family":"Guo","sequence":"first","affiliation":[{"name":"Nanjing Research Institute of Electronics Technology, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Nanjing Research Institute of Electronics Technology, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Zheng","sequence":"additional","affiliation":[{"name":"Nanjing Research Institute of Electronics Technology, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2015.81"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.156"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref30","first-page":"152","article-title":"Learning dynamic memory networks for object tracking","author":"yang","year":"2018","journal-title":"In Proc European Conf Comp Vis"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7532398"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.129"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299094"},{"key":"ref12","first-page":"4310","article-title":"Learning spatially regularized correlation filters for visual tracking","author":"danelljan","year":"2016","journal-title":"Proc IEEE Int Conf Comput Vision"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2016.2601691"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.352"},{"key":"ref15","first-page":"472","article-title":"Beyond correlation filters: Learning continuous convolution operators for visual tracking","author":"danelljan","year":"2016","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.733"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00515"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729893"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2388226"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.235"},{"article-title":"An experimental survey on correlation filter-based tracking","year":"2015","author":"chen","key":"ref4"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.513"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"1442","DOI":"10.1109\/TPAMI.2013.230","article-title":"Visual tracking: An experimental survey","volume":"36","author":"smeulders","year":"2014","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539960"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00057"},{"key":"ref5","first-page":"702","article-title":"Exploiting the circulant structure of tracking-by-detection with kernels","author":"henriques","year":"2012","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref8","first-page":"254","article-title":"A scale adaptive kernel correlation filter tracker with feature integration","author":"li","year":"2014","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref7","first-page":"65.1","article-title":"Accurate scale estimation for robust visual tracking","author":"danelljan","year":"2014","journal-title":"Proc of Brit Machine Vision Conf"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.312"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2345390"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/1177352.1177355"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00552"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.531"},{"key":"ref21","first-page":"850","article-title":"Fully-convolutional Siamese networks for object tracking","author":"bertinetto","year":"2016","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref24","first-page":"597","article-title":"Online tracking by learning discriminative saliency map with convolutional neural network","author":"hong","year":"2015","journal-title":"ICML"},{"key":"ref23","first-page":"188","article-title":"MEEM: Robust tracking via multiple experts using entropy minimization","author":"zhang","year":"2014","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2015.84"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.158"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/97\/8966529\/08979445.pdf?arnumber=8979445","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,5]],"date-time":"2025-09-05T18:28:34Z","timestamp":1757096914000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8979445\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/lsp.2020.2971387","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"type":"print","value":"1070-9908"},{"type":"electronic","value":"1558-2361"}],"subject":[],"published":{"date-parts":[[2020]]}}}