{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T12:54:43Z","timestamp":1765976083701,"version":"3.37.3"},"reference-count":12,"publisher":"Wiley","license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National High Technology Research and Development Program of China","award":["2013AA100305","61174090","DBI-0939454"],"award-info":[{"award-number":["2013AA100305","61174090","DBI-0939454"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2013AA100305","61174090","DBI-0939454"],"award-info":[{"award-number":["2013AA100305","61174090","DBI-0939454"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2013AA100305","61174090","DBI-0939454"],"award-info":[{"award-number":["2013AA100305","61174090","DBI-0939454"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2016]]},"abstract":"<jats:p>In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan\u2019s JAFFE and CMU\u2019s CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result.<\/jats:p>","DOI":"10.1155\/2016\/5687602","type":"journal-article","created":{"date-parts":[[2016,1,4]],"date-time":"2016-01-04T16:01:03Z","timestamp":1451923263000},"page":"1-12","source":"Crossref","is-referenced-by-count":5,"title":["A Modified Sparse Representation Method for Facial Expression Recognition"],"prefix":"10.1155","volume":"2016","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Control Science and Engineering, School of Electronics and Information Engineering, Tongji University, Shanghai 200092, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"LiHong","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Control Science and Engineering, School of Electronics and Information Engineering, Tongji University, Shanghai 200092, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"issue":"3","key":"1","first-page":"9","volume":"21","year":"2008","journal-title":"American Society of Mechanical Engineers"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1093\/iwc\/iwt057"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/s0031-3203(02)00052-3"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/msp.2007.914731"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2008.79"},{"issue":"8","key":"9","first-page":"440","volume":"11","year":"2012","journal-title":"WSEAS Transactions on Systems"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.e95.d.2347"},{"issue":"3","key":"11","first-page":"82","volume":"4","year":"2013","journal-title":"International Journal of Advanced Computer Science & Applications"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2014.03.006"},{"key":"13","first-page":"433","volume":"4","year":"2014","journal-title":"Applied Mechanics and Materials"},{"issue":"18","key":"16","first-page":"188","volume":"37","year":"2011","journal-title":"Computer Engineering"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2336549"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2016\/5687602.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2016\/5687602.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2016\/5687602.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2016,7,26]],"date-time":"2016-07-26T12:53:20Z","timestamp":1469537600000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/cin\/2016\/5687602\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"references-count":12,"alternative-id":["5687602","5687602"],"URL":"https:\/\/doi.org\/10.1155\/2016\/5687602","relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"type":"print","value":"1687-5265"},{"type":"electronic","value":"1687-5273"}],"subject":[],"published":{"date-parts":[[2016]]}}}