{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:16:16Z","timestamp":1740147376729,"version":"3.37.3"},"reference-count":18,"publisher":"Wiley","license":[{"start":{"date-parts":[[2018,7,15]],"date-time":"2018-07-15T00:00:00Z","timestamp":1531612800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation Projects of China","doi-asserted-by":"crossref","award":["61562048","61562047"],"award-info":[{"award-number":["61562048","61562047"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation Projects of China","doi-asserted-by":"crossref","award":["61562048","61562047"],"award-info":[{"award-number":["61562048","61562047"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advances in Multimedia"],"published-print":{"date-parts":[[2018,7,15]]},"abstract":"<jats:p>Person re-identification, aiming to identify the same pedestrian images across disjoint camera views, is a key technique of intelligent video surveillance. Although existing methods have developed both theories and experimental results, most of effective ones pertain to fully supervised training styles, which suffer the small sample size (SSS) problem a lot, especially in label-insufficient practical applications. To bridge SSS problem and learning model with small labels, a novel semisupervised co-metric learning framework is proposed to learn a discriminative Mahalanobis-like distance matrix for label-insufficient person re-identification. Different from typical co-training task that contains multiview data originally, single-view person images are firstly decomposed into pseudo two views, and then metric learning models are produced and jointly updated based on both pseudo-labels and references iteratively. Experiments carried out on three representative person re-identification datasets show that the proposed method performs better than state of the art and possesses low label sensitivity.<\/jats:p>","DOI":"10.1155\/2018\/3586191","type":"journal-article","created":{"date-parts":[[2018,7,15]],"date-time":"2018-07-15T19:31:35Z","timestamp":1531683095000},"page":"1-9","source":"Crossref","is-referenced-by-count":5,"title":["Co-Metric Learning for Person Re-Identification"],"prefix":"10.1155","volume":"2018","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9395-5863","authenticated-orcid":true,"given":"Qingming","family":"Leng","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Jiujiang University, Jiujiang 332000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2496139"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2007.893339"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2011.2173323"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2005.854437"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2011.2131639"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2014.2362520"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.246"},{"journal-title":"Computer Science\u2014Computer Vision and Pattern Recognition","year":"2016","key":"19"},{"journal-title":"In IEEE International Conference on Pattern Recognition (ICPR' 14)","year":"2014","key":"22"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2013.2255413"},{"issue":"8","key":"32","doi-asserted-by":"crossref","first-page":"1350","DOI":"10.1109\/TCSVT.2014.2305519","volume":"24","year":"2014","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2505083"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(99)00139-9"},{"key":"46","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2792062"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2563981"},{"key":"9","first-page":"89","volume":"17","year":"2004","journal-title":"Advances in Neural Information Processing Systems"},{"key":"38","first-page":"247","volume":"56","year":"2014","journal-title":"Advances in Computer Vision and Pattern Recognition"},{"issue":"4","key":"35","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1142\/S0218001493000339","volume":"7","year":"1993","journal-title":"International Journal of Pattern Recognition and Artificial Intelligence"}],"container-title":["Advances in Multimedia"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/am\/2018\/3586191.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/am\/2018\/3586191.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/am\/2018\/3586191.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,7,15]],"date-time":"2018-07-15T19:31:44Z","timestamp":1531683104000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/am\/2018\/3586191\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,15]]},"references-count":18,"alternative-id":["3586191","3586191"],"URL":"https:\/\/doi.org\/10.1155\/2018\/3586191","relation":{},"ISSN":["1687-5680","1687-5699"],"issn-type":[{"type":"print","value":"1687-5680"},{"type":"electronic","value":"1687-5699"}],"subject":[],"published":{"date-parts":[[2018,7,15]]}}}