{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T06:10:23Z","timestamp":1776060623805,"version":"3.50.1"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2018,9,1]],"date-time":"2018-09-01T00:00:00Z","timestamp":1535760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61271023"],"award-info":[{"award-number":["61271023"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772054"],"award-info":[{"award-number":["61772054"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1109\/tits.2017.2761901","type":"journal-article","created":{"date-parts":[[2017,11,20]],"date-time":"2017-11-20T19:07:18Z","timestamp":1511204838000},"page":"2826-2844","source":"Crossref","is-referenced-by-count":15,"title":["Infrared Pedestrian Segmentation Through Background Likelihood and Object-Biased Saliency"],"prefix":"10.1109","volume":"19","author":[{"given":"Lu","family":"Li","sequence":"first","affiliation":[]},{"given":"Fugen","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6115-8237","authenticated-orcid":false,"given":"Xiangzhi","family":"Bai","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/0734-189X(85)90125-2"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1975.1055330"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2516342"},{"key":"ref32","first-page":"957","article-title":"Saliency-based automatic target detection in forward looking infrared images","author":"li","year":"2009","journal-title":"Proc IEEE Int Conf Image Process (ICIP)"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2014.01.117"},{"key":"ref30","first-page":"1","article-title":"Multiple features based low-contrast infrared ship image segmentation using fuzzy inference system","author":"wang","year":"2014","journal-title":"Proc IEEE Int Conf Digit Image Comput Techn Appl (DICTA)"},{"key":"ref37","first-page":"281","article-title":"Some methods for classification and analysis of multivariate observations","volume":"1","author":"macqueen","year":"1967","journal-title":"Proc 5th Berkeley Symp Math Stat Probab"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1979.4310076"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1977.tb01600.x"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.03.005"},{"key":"ref60","author":"hou","year":"2016","journal-title":"Deeply supervised salient object detection with short connections[J]"},{"key":"ref62","first-page":"748","article-title":"Normalized cut meets MRF","author":"tang","year":"2016","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2456505"},{"key":"ref28","first-page":"510","article-title":"A simple and efficient saliency extraction method based on multi-scale horizon-directional filter for infrared dim small target detection","volume":"8004","author":"xia","year":"2011","journal-title":"Proc SPIE"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1109\/LGRS.2012.2211094","article-title":"A robust directional saliency-based method for infrared small-target detection under various complex backgrounds","volume":"10","author":"qi","year":"2013","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"ref29","first-page":"4264","article-title":"An associative saliency segmentation method for infrared targets","author":"zhang","year":"2013","journal-title":"Proc 20th IEEE Int Conf Image Process (ICIP)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2004.838222"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MVA.2015.7153177"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.370"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.209"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.1273918"},{"key":"ref24","first-page":"110","article-title":"Saliency detection via cellular automata","author":"qin","year":"2015","journal-title":"Proc IEEE Int Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1109\/LSP.2014.2323407","article-title":"Saliency detection with multi-scale superpixels","volume":"21","author":"tong","year":"2014","journal-title":"IEEE Signal Process Lett"},{"key":"ref26","first-page":"402","article-title":"Small target detection using center-surround difference with locally adaptive threshold","author":"sun","year":"2005","journal-title":"Proc 4th Int Symp Image Signal Process Anal"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459462"},{"key":"ref50","first-page":"182","article-title":"Resolution and contrast enhancement techniques for grey level, color image and satellite image","author":"bidwai","year":"2015","journal-title":"Proc Int Conf Inf Process (ICIP)"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298731"},{"key":"ref59","first-page":"839","article-title":"Background prior and boundary weight-based pedestrian segmentation in infrared images","author":"li","year":"2016","journal-title":"Proc IEEE Int Conf Image Process (ICIP)"},{"key":"ref58","first-page":"67","author":"richard","year":"2003","journal-title":"Pattern Recognition"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/34.868677"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2569159"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2539684"},{"key":"ref54","first-page":"797","article-title":"Pedestrian tracking using thermal infrared imaging","volume":"6206","author":"goubet","year":"2006","journal-title":"Proc SPIE"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574710000299"},{"key":"ref52","first-page":"5455","article-title":"Visual saliency based on multiscale deep features","author":"li","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref10","first-page":"1","article-title":"Saliency detection based on frequency and spatial domain analysis","author":"li","year":"2011","journal-title":"Proc Brit Mach Vis Conf (BMVC)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.5244\/C.25.110"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZY.1993.327400"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.272"},{"key":"ref14","first-page":"3166","article-title":"Saliency detection via graph-based manifold ranking","volume":"9","author":"yang","year":"2013","journal-title":"Proc IEEE Int Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1109\/TPAMI.2010.70","article-title":"Learning to detect a salient object","volume":"33","author":"liu","year":"2011","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.360"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.271"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.193"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2004.1334006"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2004.834875"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2009.2018961"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2010.09.006"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2010.03.005"},{"key":"ref8","first-page":"3118","article-title":"Salient object detection: A survey","volume":"16","author":"borji","year":"2014","journal-title":"ArXiv eprint"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2013.08.001"},{"key":"ref49","first-page":"1817","article-title":"Remote sensing image fusion based on average gradient of wavelet transform","volume":"4","author":"wu","year":"2005","journal-title":"Proc IEEE Int Conf Mechatronics Autom"},{"key":"ref9","first-page":"1597","article-title":"Frequency-tuned salient region detection","author":"achanta","year":"2009","journal-title":"Proc IEEE Int Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref46","first-page":"645","article-title":"Visual saliency detection based on Bayesian model","author":"xie","year":"2011","journal-title":"Proc IEEE Int Conf Image Process (ICIP)"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2016.2544781"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2012.03.004"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ACVMOT.2005.14"},{"key":"ref42","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1117\/1.1631315","article-title":"Survey over image thresholding techniques and quantitative performance evaluation","volume":"13","author":"sezgin","year":"2004","journal-title":"J Electron Imag"},{"key":"ref41","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1016\/j.patrec.2004.11.002","article-title":"Infrared image segmentation with 2-D maximum entropy method based on particle swarm optimization (PSO)","volume":"26","author":"du","year":"2005","journal-title":"Pattern Recognit Lett"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1142\/S021821301360004X"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.177"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/8458340\/08115187.pdf?arnumber=8115187","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T11:45:57Z","timestamp":1643197557000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8115187\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9]]},"references-count":62,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tits.2017.2761901","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9]]}}}