{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T16:14:09Z","timestamp":1761581649834,"version":"3.37.3"},"reference-count":15,"publisher":"Wiley","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Foundation of Young Resherve Talents Project in Scientific and Technical Bureau in Harbin","award":["2017RAQXJ134","61573114"],"award-info":[{"award-number":["2017RAQXJ134","61573114"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2017RAQXJ134","61573114"],"award-info":[{"award-number":["2017RAQXJ134","61573114"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Electrical and Computer Engineering"],"published-print":{"date-parts":[[2018]]},"abstract":"<jats:p>We propose a more effective tracking algorithm which can work robustly in a complex scene such as illumination, appearance change, and partial occlusion. The algorithm is based on an improved particle filter which used the efficient design of observation model. Predefined convolutional filters are used to extract the high-order features. The global representation is generated by combining local features without changing their structures and space arrangements. It not only increases the feature invariance, but also maintains the specificity. The extracted feature from convolution network is introduced into particle filter algorithm. The observation model is constructed by fusing the color feature of the target and a set of features from templates which are extracted by convolutional networks without training in our paper. It is fused with the features extracted from convolutional network for tracking. In the process of tracking, the template is updated in real time, and then the robustness of the algorithm is improved. Experiments show that the algorithm can achieve an ideal tracking effect when the targets are in a complex environment.<\/jats:p>","DOI":"10.1155\/2018\/5381962","type":"journal-article","created":{"date-parts":[[2018,1,9]],"date-time":"2018-01-09T18:49:48Z","timestamp":1515523788000},"page":"1-9","source":"Crossref","is-referenced-by-count":6,"title":["Target Tracking via Particle Filter and Convolutional Network"],"prefix":"10.1155","volume":"2018","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4490-8454","authenticated-orcid":true,"given":"Hongxia","family":"Chu","sequence":"first","affiliation":[{"name":"College of Automation, Harbin Engineering University, Harbin, China"},{"name":"College of Electrical and Information Engineering, Heilongjiang Institute of Technology, Harbin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kejun","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Automation, Harbin Engineering University, Harbin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianglei","family":"Xing","sequence":"additional","affiliation":[{"name":"College of Automation, Harbin Engineering University, Harbin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1145\/1177352.1177355"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.10.009"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2003.1233903"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-007-0075-7"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2456899"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1007\/s11554-012-0315-0"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-014-0409-3"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.4218\/etrij.16.0115.0181"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2531283"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2510583"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.01.098"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_45"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/756\/1\/012011"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-47969-4_44"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.06.048"}],"container-title":["Journal of Electrical and Computer Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2018\/5381962.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2018\/5381962.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2018\/5381962.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,1,9]],"date-time":"2018-01-09T18:49:51Z","timestamp":1515523791000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/jece\/2018\/5381962\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":15,"alternative-id":["5381962","5381962"],"URL":"https:\/\/doi.org\/10.1155\/2018\/5381962","relation":{},"ISSN":["2090-0147","2090-0155"],"issn-type":[{"type":"print","value":"2090-0147"},{"type":"electronic","value":"2090-0155"}],"subject":[],"published":{"date-parts":[[2018]]}}}