{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T11:30:46Z","timestamp":1774611046161,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2011,10,11]],"date-time":"2011-10-11T00:00:00Z","timestamp":1318291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Facial expression recognition is an interesting and challenging subject. Considering the nonlinear manifold structure of facial images, a new kernel-based manifold learning method, called kernel discriminant isometric mapping (KDIsomap), is proposed. KDIsomap aims to nonlinearly extract the discriminant information by maximizing the interclass scatter while minimizing the intraclass scatter in a reproducing kernel Hilbert space. KDIsomap is used to perform nonlinear dimensionality reduction on the extracted local binary patterns (LBP) facial features, and produce low-dimensional discrimimant embedded data representations with striking performance improvement on facial expression recognition tasks. The nearest neighbor classifier with the Euclidean metric is used for facial expression classification. Facial expression recognition experiments are performed on two popular facial expression databases, i.e., the JAFFE database and the Cohn-Kanade database. Experimental results indicate that KDIsomap obtains the best accuracy of 81.59% on the JAFFE database, and 94.88% on the Cohn-Kanade database. KDIsomap outperforms the other used methods such as principal component analysis (PCA), linear discriminant analysis (LDA), kernel principal component analysis (KPCA), kernel linear discriminant analysis (KLDA) as well as kernel isometric mapping (KIsomap).<\/jats:p>","DOI":"10.3390\/s111009573","type":"journal-article","created":{"date-parts":[[2011,10,11]],"date-time":"2011-10-11T12:52:32Z","timestamp":1318337552000},"page":"9573-9588","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":89,"title":["Facial Expression Recognition Based on Local Binary Patterns and Kernel Discriminant Isomap"],"prefix":"10.3390","volume":"11","author":[{"given":"Xiaoming","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Computer Science, Taizhou University, Taizhou 317000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2011,10,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/79.911197","article-title":"Emotion recognition in human-computer interaction","volume":"18","author":"Cowie","year":"2001","journal-title":"IEEE Signal Proc. Mag"},{"key":"ref_2","unstructured":"Tian, Y, Kanade, T, and Cohn, J (2005). Handbook of Face Recognition, Springer."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1023\/B:VISI.0000013087.49260.fb","article-title":"Robust real-time face detection","volume":"57","author":"Viola","year":"2004","journal-title":"Int. J. Comput. Vis"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Turk, MA, and Pentland, AP (1991, January 3\u20136). Face recognition using eigenfaces. Maui, HI, USA.","DOI":"10.1162\/jocn.1991.3.1.71"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1109\/34.598228","article-title":"Eigenfaces vs. fisherfaces: Recognition using class specific linear projection","volume":"19","author":"Belhumeur","year":"1997","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1109\/29.1644","article-title":"Complete discrete 2-d gabor transforms by neural networks for image analysis and compression","volume":"36","author":"Daugman","year":"1988","journal-title":"IEEE Trans. Acoust. Speech Signal Process"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/s10044-006-0033-y","article-title":"A review on gabor wavelets for face recognition","volume":"9","author":"Shen","year":"2006","journal-title":"Pattern Anal. Appl"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1016\/j.imavis.2006.05.002","article-title":"Gabor wavelets and general discriminant analysis for face identification and verification","volume":"25","author":"Shen","year":"2007","journal-title":"Image Vis. Comput"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.1109\/34.817413","article-title":"Automatic classification of single facial images","volume":"21","author":"Lyons","year":"1999","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","article-title":"Multiresolution gray scale and rotation invariant texture analysis with local binary patterns","volume":"24","author":"Ojala","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_11","unstructured":"Shan, C, Gong, S, and McOwan, P (2005, January 11\u201314). Robust facial expression recognition using local binary patterns. Genoa, Italy."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1016\/j.imavis.2008.08.005","article-title":"Facial expression recognition based on local binary patterns: A comprehensive study","volume":"27","author":"Shan","year":"2009","journal-title":"Image Vis. Comput"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1016\/j.cviu.2010.12.001","article-title":"Local binary patterns for multi-view facial expression recognition","volume":"115","author":"Moore","year":"2011","journal-title":"Comput. Vis. Image. Und"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1109\/34.908962","article-title":"Recognizing action units for facial expression analysis","volume":"23","author":"Tian","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1109\/TIP.2006.884954","article-title":"Facial expression recognition in image sequences using geometric deformation features and support vector machines","volume":"16","author":"Kotsia","year":"2007","journal-title":"IEEE Trans. Image Process"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"974","DOI":"10.1109\/34.799905","article-title":"Classifying facial actions","volume":"21","author":"Donato","year":"1999","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1109\/TSMCB.2005.859075","article-title":"Dynamics of facial expression: Recognition of facial actions and their temporal segments from face profile image sequences","volume":"36","author":"Pantic","year":"2006","journal-title":"IEEE Trans. Syst. Man. Cybern. Part B"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/S1077-3142(03)00081-X","article-title":"Facial expression recognition from video sequences: Temporal and static modeling","volume":"91","author":"Cohen","year":"2003","journal-title":"Comput. Vis. Image. Und"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","article-title":"Nonlinear dimensionality reduction by locally linear embedding","volume":"290","author":"Roweis","year":"2000","journal-title":"Science"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","article-title":"A global geometric framework for nonlinear dimensionality reduction","volume":"290","author":"Tenenbaum","year":"2000","journal-title":"Science"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1016\/j.imavis.2005.08.006","article-title":"Manifold based analysis of facial expression","volume":"24","author":"Chang","year":"2006","journal-title":"Image Vis. Comput"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1016\/j.patcog.2008.10.010","article-title":"Natural facial expression recognition using differential-aam and manifold learning","volume":"42","author":"Cheon","year":"2009","journal-title":"Pattern Recogn"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1016\/j.patcog.2006.04.025","article-title":"Robust kernel isomap","volume":"40","author":"Choi","year":"2007","journal-title":"Pattern Recogn"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1162\/089976698300017467","article-title":"Nonlinear component analysis as a kernel eigenvalue problem","volume":"10","author":"Scholkopf","year":"1998","journal-title":"Neural Comput"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ham, J, Lee, D, Mika, S, and Scholkopf, B (2004, January 4\u20138). A kernel view of the dimensionality reduction of manifolds. Banff, AB, Canada.","DOI":"10.1145\/1015330.1015417"},{"key":"ref_26","unstructured":"Kanade, T, Tian, Y, and Cohn, J (2000, January 26\u201330). Comprehensive database for facial expression analysis. Grenoble, France."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Campadelli, P, Lanzarotti, R, Lipori, G, and Salvi, E (2005, January 6\u20138). Face and facial feature localization. Cagliari, Italy.","DOI":"10.1007\/11553595_123"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2037","DOI":"10.1109\/TPAMI.2006.244","article-title":"Face description with local binary patterns: Application to face recognition","volume":"28","author":"Ahonen","year":"2006","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2385","DOI":"10.1162\/089976600300014980","article-title":"Generalized discriminant analysis using a kernel approach","volume":"12","author":"Baudat","year":"2000","journal-title":"Neural Comput"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/11\/10\/9573\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:57:37Z","timestamp":1760219857000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/11\/10\/9573"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,10,11]]},"references-count":29,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2011,10]]}},"alternative-id":["s111009573"],"URL":"https:\/\/doi.org\/10.3390\/s111009573","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,10,11]]}}}