{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T19:28:38Z","timestamp":1769714918817,"version":"3.49.0"},"reference-count":12,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2023,4,3]]},"abstract":"<jats:p>Person re-identification identify a specific person in surveillance network by similarity measurement between images of different camera views. However, existing metric learning based methods suffer from over-fitting problem. To solve this problem, a resampled linear discriminant analysis (LDA) method was proposed based on the statistical and topological characteristics of pedestrian images. This method utilized the k-nearest neighbours to form potential positive sample pairs. The potential positive pairs are used to improve the metric model and generalize the metric model to the test data. By minimizing the inter-class divergence of potential positive sample pairs, a semi-supervised re-sampling LDA person re-identification algorithm was established. It was then tested on the VIPeR, CUHK01 and Market 1501datasets. The results show that the proposed method achieves the best performance compared to some available methods. Especially, the proposed method outplays the best comparison method by 0.6% and 5.76% at rank-1 identification rate on the VIPeR and CUHK01 datasets respectively. At the same time, the improved LDA algorithm has improved the rank-1 identification accuracy of traditional LDA method by 9.36% and 32.11% on these two datasets respectively. Besides, the proposed method is limited to Market-1501 dataset when the test data is of large size.<\/jats:p>","DOI":"10.3233\/jifs-220924","type":"journal-article","created":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T10:46:08Z","timestamp":1668768368000},"page":"5647-5658","source":"Crossref","is-referenced-by-count":0,"title":["Semi-supervised LDA pedestrian re-identification algorithm based on K-nearest neighbor resampling"],"prefix":"10.1177","volume":"44","author":[{"given":"Bin","family":"Li","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Wuhan Polytechnic University, Wuhan Hubei, China"}]},{"given":"Ying","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Wuhan Polytechnic University, Wuhan Hubei, China"}]},{"given":"Xiaopeng","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan Hubei, China"}]},{"given":"Qinghua","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Wuhan Polytechnic University, Wuhan Hubei, China"}]},{"given":"Zhigang","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Wuhan Polytechnic University, Wuhan Hubei, China"}]}],"member":"179","reference":[{"issue":"5","key":"10.3233\/JIFS-220924_ref1","doi-asserted-by":"crossref","first-page":"1060","DOI":"10.1109\/TNNLS.2014.2333751","article-title":"Learning to track multiple targets","volume":"26","author":"Liu","year":"2015","journal-title":"IEEE Trans on Neural Networks & Learning Systems"},{"key":"10.3233\/JIFS-220924_ref4","doi-asserted-by":"crossref","unstructured":"Zhang Z. , Chen Y. , Saligrama V. A Novel Visual Word Cooccurrence Model for Person Re-identification, in:Workshop at the European Conference on Computer Vision, Springer International Publishing, (2014), pp. 122\u2013133.","DOI":"10.1007\/978-3-319-16199-0_9"},{"issue":"9","key":"10.3233\/JIFS-220924_ref6","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1007\/978-3-662-45643-9_57","article-title":"Salient Color Names for Person Re-identification","volume":"8689","author":"Yang","year":"2014","journal-title":"State Key Laboratory of Pattern Recognition"},{"issue":"3","key":"10.3233\/JIFS-220924_ref12","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1109\/TPAMI.2012.138","article-title":"Reidentification by relative distance comparison","volume":"35","author":"Zheng","year":"2013","journal-title":"IEEE Trans on Pattern Analysis and Machine Intelligence"},{"issue":"7","key":"10.3233\/JIFS-220924_ref16","first-page":"1612","article-title":"Pedestrian re-identification algorithm based on statistical inference","volume":"36","author":"Du","year":"2014","journal-title":"Journal of Electronics and Information Technology"},{"key":"10.3233\/JIFS-220924_ref17","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.patrec.2020.12.017","article-title":"SSS-PR: A short survey of surveys in person re-identification","volume":"143","author":"Yaghoubi","year":"2021","journal-title":"Pattern Recognition Letters"},{"issue":"99","key":"10.3233\/JIFS-220924_ref18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TPAMI.2021.3054384","article-title":"Deep learning for person reidentification: A survey and outlook","author":"Ye","year":"2021","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"1","key":"10.3233\/JIFS-220924_ref19","first-page":"207","article-title":"Distance metric learning for large margin nearest neighbor classification","volume":"10","author":"Weinberger","year":"2009","journal-title":"The Journal of Machine Learning Research"},{"issue":"3","key":"10.3233\/JIFS-220924_ref20","doi-asserted-by":"crossref","first-page":"1363","DOI":"10.1109\/TIP.2017.2651364","article-title":"Super-resolution Person re-identification with semi-coupled low-rank discriminant dictionary learning","volume":"26","author":"Jing","year":"2017","journal-title":"IEEE Trans on Image Processing"},{"issue":"7","key":"10.3233\/JIFS-220924_ref26","doi-asserted-by":"crossref","first-page":"3516","DOI":"10.1109\/TIP.2019.2898567","article-title":"Quadruplet network with oneshot learning for fast visual object tracking","volume":"28","author":"Dong","year":"2019","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.3233\/JIFS-220924_ref27","unstructured":"Yu H. , Wu A. , Zheng W. Unsupervised person reidentification by deep asymmetric metric embedding,, IEEE Transactions on Pattern Analysis and Machine Intelligence PP(99) (2018), 1\u00e2\u0102\u015e"},{"key":"10.3233\/JIFS-220924_ref29","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.cogsys.2018.04.003","article-title":"A deep model with combined losses for person re-identification","volume":"54","author":"Wu","year":"2019","journal-title":"Cognitive Systems Research"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-220924","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T08:59:16Z","timestamp":1769677156000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-220924"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,3]]},"references-count":12,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/jifs-220924","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,3]]}}}