{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T00:15:51Z","timestamp":1768436151080,"version":"3.49.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["61802267"],"award-info":[{"award-number":["61802267"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["61773328"],"award-info":[{"award-number":["61773328"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["61732011"],"award-info":[{"award-number":["61732011"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["61703283"],"award-info":[{"award-number":["61703283"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015805","name":"Shenzhen Municipal Science and Technology Innovation Council","doi-asserted-by":"crossref","award":["JCYJ20180305124834854"],"award-info":[{"award-number":["JCYJ20180305124834854"]}],"id":[{"id":"10.13039\/501100015805","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100015805","name":"Shenzhen Municipal Science and Technology Innovation Council","doi-asserted-by":"crossref","award":["JCYJ20190813100801664"],"award-info":[{"award-number":["JCYJ20190813100801664"]}],"id":[{"id":"10.13039\/501100015805","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s11042-020-09802-9","type":"journal-article","created":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T07:02:36Z","timestamp":1600844556000},"page":"3729-3748","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Relaxed local preserving regression for image feature extraction"],"prefix":"10.1007","volume":"80","author":[{"given":"Jiaqi","family":"Bao","sequence":"first","affiliation":[]},{"given":"Zhihui","family":"Lai","sequence":"additional","affiliation":[]},{"given":"Xuechen","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,23]]},"reference":[{"key":"9802_CR1","volume-title":"Convex analysis and optimization","author":"DP Bertsekas","year":"2003","unstructured":"Bertsekas DP, Nedi A, Ozdaglar AE (2003) Convex analysis and optimization. Athena Scientific, Belmont"},{"issue":"11","key":"9802_CR2","doi-asserted-by":"publisher","first-page":"3608","DOI":"10.1109\/TIP.2006.881945","volume":"15","author":"D Cai","year":"2006","unstructured":"Cai D, He X, Han J, Member S (2006) Orthogonal laplacianfaces for face recognition. IEEE Trans Image Process 15(11):3608\u20133614","journal-title":"IEEE Trans Image Process"},{"key":"9802_CR3","doi-asserted-by":"crossref","unstructured":"Cai D, Wang X, He X (2009) Probabilistic dyadic data analysis with local and global consistency. In: ICML","DOI":"10.1145\/1553374.1553388"},{"key":"9802_CR4","unstructured":"Campos T E, Babu B R,Varma M (2009) Character recognition innatural images. In: VISAPP"},{"key":"9802_CR5","doi-asserted-by":"crossref","unstructured":"Cheng L, Yang M (2018) Graph regularized weighted low-rank representation for image clustering. In: CCC","DOI":"10.23919\/ChiCC.2018.8483648"},{"key":"9802_CR6","doi-asserted-by":"crossref","unstructured":"Deng T, Liu J, Wang N (2016) Locally linear embedding preserving local neighborhood. In: ICNC-FSKD","DOI":"10.1109\/FSKD.2016.7603213"},{"key":"9802_CR7","unstructured":"Ebied RM (2012) Feature extraction using PCA and Kernel-PCA for face recognition. In: INFOS"},{"issue":"4","key":"9802_CR8","doi-asserted-by":"publisher","first-page":"1006","DOI":"10.1109\/TNNLS.2017.2648880","volume":"29","author":"X Fang","year":"2018","unstructured":"Fang X, Xu Y, Li X, Lai Z, Wong WK, Fang B (2018) Regularized label relaxation linear regression. IEEE Trans Neural Netw Learn Syst 29(4):1006\u20131018","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"6","key":"9802_CR9","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1109\/34.927464","volume":"23","author":"AS Georghiades","year":"2001","unstructured":"Georghiades AS, Member S, Belhumeur PN (2001) From few to many : illumination cone models for face recognition under variable lighting and pose. IEEE Trans Pattern Anal Mach Intell 23(6):643\u2013660","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9802_CR10","doi-asserted-by":"crossref","unstructured":"Gui J, Sun Z, Hou G, Tan T (2014) An optimal set of code words and correntropy for rotated least squares regression. In: IJCB","DOI":"10.1109\/BTAS.2014.6996222"},{"key":"9802_CR11","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1016\/j.neucom.2017.08.070","volume":"275","author":"L Han","year":"2018","unstructured":"Han L, Wu Z, Zeng K, Yang X (2018) Online multilinear principal component analysis. Neurocomputing 275:888\u2013896","journal-title":"Neurocomputing"},{"issue":"2","key":"9802_CR12","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1109\/TCSVT.2018.2890511","volume":"30","author":"N Han","year":"2020","unstructured":"Han N, Wu J, Fang X, Wong WK, Xu Y, Yang J, Li X (2020) Double relaxed regression for image classification. IEEE Trans Circuits Syst Video Technol 30(2):307\u2013319","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"9802_CR13","first-page":"153","volume":"16","author":"X He","year":"2010","unstructured":"He X, Niyogi P (2010) Locality preserving projections. Neural Inf Process Syst 16:153","journal-title":"Neural Inf Process Syst"},{"issue":"3","key":"9802_CR14","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1109\/TPAMI.2005.55","volume":"27","author":"X He","year":"2005","unstructured":"He X, Yan S, Hu Y, Niyogi P, Zhang H (2005) Face recognition using laplacianfaces. IEEE Trans Pattern Anal Mach Intell 27(3):328\u2013340","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9802_CR15","unstructured":"He X, Cai D, Yan S, Zhang HJ (2005) Neighborhood preserving embedding. In:ICCV"},{"key":"9802_CR16","unstructured":"Huang G B, Mattar M, Berg T, Learned-miller E (2007) Labeled faces in the wild : a database for studying face recognition in unconstrained environments. Tech. Rep. 07-49, Univ. Massachusetts, Amherst."},{"key":"9802_CR17","doi-asserted-by":"crossref","unstructured":"Keyhanian S, Nasersharif B (2014) Laplacian eigenmaps modification using adaptive graph for pattern recognition. In: BIHTEL","DOI":"10.1109\/ISTEL.2014.7000664"},{"key":"9802_CR18","doi-asserted-by":"crossref","unstructured":"Leng L, Zhang J, Chen G, Khan MK, Alghathbar K (2011) Two-directional two-dimensional random projection and its variations for face and palmprint recognition. In: ICCSA, pp 458\u2013470","DOI":"10.1007\/978-3-642-21934-4_37"},{"key":"9802_CR19","doi-asserted-by":"crossref","unstructured":"Leng L, Zhang S, Bi X, Khan M K (2012) Two-dimensional cancelable biometric scheme. In: ICWAPR","DOI":"10.1109\/ICWAPR.2012.6294772"},{"key":"9802_CR20","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.neucom.2019.01.049","volume":"337","author":"C Li","year":"2019","unstructured":"Li C, Shang M, Shao Y, Xu Y, Liu L, Wang Z (2019) Sparse L1-norm two dimensional linear discriminant analysis via the generalized elastic net regularization. Neurocomputing 337:80\u201396","journal-title":"Neurocomputing"},{"issue":"9","key":"9802_CR21","doi-asserted-by":"publisher","first-page":"1037","DOI":"10.1016\/j.patrec.2013.01.030","volume":"34","author":"Z Liang","year":"2013","unstructured":"Liang Z, Xia S, Zhou Y, Zhang L, Li Y (2013) Feature extraction based on Lp-norm generalized principal component analysis. Pattern Recogn Lett 34(9):1037\u20131045","journal-title":"Pattern Recogn Lett"},{"key":"9802_CR22","doi-asserted-by":"crossref","unstructured":"Liu X, Yin J, Feng Z, Dong J, Wang L (2007) Orthogonal neighborhood preserving embedding for face recognition. In:ICIP","DOI":"10.1109\/ICIP.2007.4378909"},{"issue":"1","key":"9802_CR23","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1109\/TPAMI.2012.88","volume":"35","author":"G Liu","year":"2013","unstructured":"Liu G, Lin Z, Member S, Yan S, Member S (2013) Robust recovery of subspace structures by low-rank representation. IEEE Trans Pattern Anal Mach Intell 35(1):171\u2013184","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"6","key":"9802_CR24","doi-asserted-by":"publisher","first-page":"510","DOI":"10.1109\/TNB.2016.2574923","volume":"15","author":"JX Liu","year":"2016","unstructured":"Liu JX, Gao YL, Zheng CH, Xu Y, Yu J (2016) Block-constraint robust principal component analysis and its application to integrated analysis of TCGA data. IEEE Trans Nano Biosci 15(6):510\u2013516","journal-title":"IEEE Trans Nano Biosci"},{"key":"9802_CR25","doi-asserted-by":"crossref","unstructured":"Liu H, Lai Z, Chen Y (2017) Joint sparse locality preserving projections. In: SMARTCOMP","DOI":"10.1007\/978-3-319-73830-7_13"},{"key":"9802_CR26","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1016\/j.patcog.2016.01.029","volume":"55","author":"GF Lu","year":"2016","unstructured":"Lu GF, Zou J, Wang Y (2016) L1-norm-based principal component analysis with adaptive regularization. Pattern Recogn 55:207\u2013214","journal-title":"Pattern Recogn"},{"key":"9802_CR27","unstructured":"Martinez AA, Benavente R (1998) The AR face database. Tech Rep Univ Autonoma Barcelona"},{"issue":"8","key":"9802_CR28","doi-asserted-by":"publisher","first-page":"3018","DOI":"10.1109\/TIP.2013.2253476","volume":"22","author":"L Maximization","year":"2013","unstructured":"Maximization L (2013) Linear discriminant analysis based on L1-norm maximization. IEEE Trans Image Process 22(8):3018\u20133027","journal-title":"IEEE Trans Image Process"},{"key":"9802_CR29","doi-asserted-by":"crossref","unstructured":"Okfalisa, Gazalba I, Mustakim, Reza N G I (2017) Comparative analysis of k-nearest neighbor and modified k-nearest neighbor algorithm for data classification. In: ICITISEE","DOI":"10.1109\/ICITISEE.2017.8285514"},{"key":"9802_CR30","doi-asserted-by":"crossref","unstructured":"Pan H, Kang Z (2018) Robust graph learning for semi-supervised classification. In: IHMSC","DOI":"10.1109\/IHMSC.2018.00068"},{"issue":"14","key":"9802_CR31","doi-asserted-by":"publisher","first-page":"1822","DOI":"10.1016\/j.patrec.2011.07.015","volume":"32","author":"J Pan","year":"2011","unstructured":"Pan J, Zhang J (2011) Large margin based nonnegative matrix factorization and partial least squares regression for face recognition. Pattern Recogn Lett 32(14):1822\u20131835","journal-title":"Pattern Recogn Lett"},{"key":"9802_CR32","doi-asserted-by":"crossref","unstructured":"Phillips PJ, Moon H, Rizvi SA, Rauss PJ (1997) The FERET evaluation methodology for face-recognition algorithms state university of new york at buffalo, amherst, NY 14260. pp 137\u2013143","DOI":"10.6028\/NIST.IR.6264"},{"key":"9802_CR33","doi-asserted-by":"crossref","unstructured":"S Shao, Tang M (2019) Semi-supervised structured sparse graph data classification. In: AIAM","DOI":"10.1109\/AIAM48774.2019.00027"},{"issue":"12","key":"9802_CR34","doi-asserted-by":"publisher","first-page":"1615","DOI":"10.1109\/TPAMI.2003.1251154","volume":"25","author":"T Sim","year":"2003","unstructured":"Sim T, Baker S, Bsat M (2003) The CMU pose, illumination, and expression database. IEEE Trans Pattern Anal Mach Intell 25(12):1615\u20131618","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"6","key":"9802_CR35","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.1109\/TPAMI.2011.184","volume":"34","author":"FDL Torre","year":"2012","unstructured":"Torre FDL (2012) A least-squares framework for component analysis. IEEE Trans Pattern Anal Mach Intell 34(6):1041\u20131055","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"9802_CR36","doi-asserted-by":"publisher","first-page":"2339","DOI":"10.1007\/s11042-013-1551-4","volume":"72","author":"N Wang","year":"2014","unstructured":"Wang N, Li Q, El-Latif AAA, Peng J, Niu X (2014) An enhanced thermal face recognition method based on multiscale complex fusion for Gabor coefficients. Multimed Tools Appl 72(3):2339\u20132358","journal-title":"Multimed Tools Appl"},{"issue":"12","key":"9802_CR37","doi-asserted-by":"publisher","first-page":"2711","DOI":"10.1109\/TNNLS.2015.2477826","volume":"27","author":"L Wang","year":"2016","unstructured":"Wang L, Zhang XY, Pan C (2016) MSDLSR: margin scalable discriminative least squares regression for multicategory classification. IEEE Trans Neural Netw Learn Syst 27(12):2711\u20132717","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"9802_CR38","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1016\/j.neucom.2016.07.044","volume":"216","author":"H Wang","year":"2016","unstructured":"Wang H, Feng L, Yu L, Zhang J (2016) Multi-view sparsity preserving projection for dimension reduction. Neurocomputing 216:286\u2013295","journal-title":"Neurocomputing"},{"key":"9802_CR39","doi-asserted-by":"crossref","unstructured":"Wang L, Liu S, Pan C (2017) Rodlsr: robust discriminative least squares regression model for multi-category classification. In: ICASSP","DOI":"10.1109\/ICASSP.2017.7952588"},{"key":"9802_CR40","doi-asserted-by":"crossref","unstructured":"Wen Y, Zhang K, Li Z, Qiao Y (2016) A discriminative feature learning approach for deep face recognition. In: ECCV","DOI":"10.1007\/978-3-319-46478-7_31"},{"issue":"2","key":"9802_CR41","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1109\/TPAMI.2008.79","volume":"31","author":"YAY Wright","year":"2009","unstructured":"Wright YAY, Ganesh A, Sastry SS, Ma Y (2009) Robust face recognition via sparse representation. IEEE Trans Pattern Anal Mach Intell 31(2):210\u2013227","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"9802_CR42","doi-asserted-by":"publisher","first-page":"1738","DOI":"10.1109\/TNNLS.2012.2212721","volume":"23","author":"S Xiang","year":"2012","unstructured":"Xiang S, Nie F, Meng G, Pan C, Zhang C (2012) Discriminative least squares regression for multiclass classification and feature selection. IEEE Trans Neural Netw Learn Syst 23(11):1738\u20131754","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"9802_CR43","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.neucom.2017.05.008","volume":"275","author":"J Xu","year":"2018","unstructured":"Xu J (2018) A weighted linear discriminant analysis framework for multi-label feature extraction. Neurocomputing 275:107\u2013120","journal-title":"Neurocomputing"},{"issue":"2","key":"9802_CR44","first-page":"569","volume":"2","author":"J Yang","year":"2009","unstructured":"Yang J, Yin W, Zhang Y, Wang Y (2009) A fast algorithm for edge-preserving variational multichannel image restoration. SIAM J Comput 2(2):569\u2013592","journal-title":"SIAM J Comput"},{"issue":"1","key":"9802_CR45","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1109\/TCSVT.2016.2596158","volume":"28","author":"Q Ye","year":"2016","unstructured":"Ye Q, Yang J, Liu F, Zhao C, Ye N, Yin T (2016) L1-norm distance linear discriminant analysis based on an effective iterative algorithm. IEEE Trans Circuits Syst Video Technol 28(1):114\u2013129","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"9802_CR46","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1016\/j.patcog.2016.08.025","volume":"61","author":"S Yi","year":"2017","unstructured":"Yi S, Lai Z, He Z, Cheung Y, Liu Y (2017) Joint sparse principal component analysis. Pattern Recogn 61:524\u2013536","journal-title":"Pattern Recogn"},{"issue":"3","key":"9802_CR47","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1109\/TPAMI.2015.2462360","volume":"38","author":"M Yin","year":"2016","unstructured":"Yin M, Gao J, Lin Z, Member S (2016) Laplacian regularized low-rank representation and its applications. IEEE Trans Pattern Anal Mach Intell 38(3):504\u2013517","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9802_CR48","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1016\/j.neucom.2017.07.064","volume":"273","author":"R Zhang","year":"2018","unstructured":"Zhang R, Nie F, Li X (2018) Feature selection under regularized orthogonal least square regression with optimal scaling. Neurocomputing 273:547\u2013553","journal-title":"Neurocomputing"},{"key":"9802_CR49","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/j.neucom.2016.07.037","volume":"216","author":"H Zhao","year":"2016","unstructured":"Zhao H, Wang Z, Nie F (2016) Orthogonal least squares regression for feature extraction. Neurocomputing 216:200\u2013207","journal-title":"Neurocomputing"},{"key":"9802_CR50","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.neucom.2012.09.015","volume":"103","author":"Y Zheng","year":"2013","unstructured":"Zheng Y, Fang B, Yan Y, Zhang T, Liu R (2013) Learning orthogonal projections for Isomap. Neurocomputing 103:149\u2013154","journal-title":"Neurocomputing"},{"issue":"2","key":"9802_CR51","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1198\/106186006X113430","volume":"15","author":"H Zou","year":"2006","unstructured":"Zou H, Hastie T, Tibshirani R (2006) Sparse principal component analysis. J Comput Graph Stat 15(2):265\u2013286","journal-title":"J Comput Graph Stat"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09802-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09802-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09802-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T23:46:59Z","timestamp":1632354419000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09802-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,23]]},"references-count":51,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["9802"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09802-9","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,23]]},"assertion":[{"value":"4 November 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 September 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 September 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"We declared that we have no financial and personal relationships with other people or organizations that can inappropriately influence on this work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}