{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T22:40:02Z","timestamp":1749854402100,"version":"3.41.0"},"reference-count":51,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,11]]},"DOI":"10.1109\/dicta.2016.7797063","type":"proceedings-article","created":{"date-parts":[[2016,12,26]],"date-time":"2016-12-26T21:44:21Z","timestamp":1482788661000},"page":"1-7","source":"Crossref","is-referenced-by-count":0,"title":["MLE-Based Learning on Grassmann Manifolds"],"prefix":"10.1109","author":[{"given":"Muhammad","family":"Ali","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junbin","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Antolovich","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref39","DOI":"10.1109\/DICTA.2013.6691493"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.1109\/TMM.2016.2557071"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1214\/ss\/1030037906"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1017\/CBO9780511619083"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1214\/ss\/1177012906"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1214\/aoms\/1177728652"},{"doi-asserted-by":"publisher","key":"ref37","DOI":"10.1007\/s11263-013-0636-x"},{"doi-asserted-by":"publisher","key":"ref36","DOI":"10.1109\/CVPR.2010.5539921"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1007\/978-3-642-15552-9_17"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1016\/j.cviu.2005.09.012"},{"key":"ref28","first-page":"1583","article-title":"Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification","volume":"8","author":"hamsici","year":"2007","journal-title":"The Journal of Machine Learning Research"},{"key":"ref27","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-21540-2","author":"chikuse","year":"2003","journal-title":"Statistics on Special Manifolds (Lecture Notes in Statistics)"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1515\/9781400830244"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1016\/j.imavis.2011.08.002"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.2197\/ipsjtcva.1.83"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1007\/s11263-015-0833-x"},{"key":"ref22","doi-asserted-by":"crossref","DOI":"10.4018\/978-1-4666-0059-1.ch017","article-title":"Manifold learning for medical image registration, segmentation and classification","author":"aljabar","year":"2012","journal-title":"Machine Learning in Computer-Aided Diagnosis"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1109\/CVPR.2008.4587733"},{"year":"1987","author":"mccullagh","journal-title":"Tensor Methods in Statistics","key":"ref24"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1214\/aoms\/1177703550"},{"year":"2000","author":"mardia","journal-title":"Directional Statistics","key":"ref26"},{"key":"ref25","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198522959.001.0001","author":"jensen","year":"1995","journal-title":"Saddlepoint Approximations"},{"doi-asserted-by":"publisher","key":"ref50","DOI":"10.1109\/ICCV.2015.468"},{"key":"ref51","article-title":"Block-Diagonal Sparse Representation by Learning a Linear Combination Dictionary for Recognition","author":"piao","year":"2016","journal-title":"arXiv 1601 01432 [cs CV]"},{"key":"ref10","first-page":"1345","article-title":"Clustering on the unit Hypersphere using von Mises-Fisher Distributions","author":"banerjee","year":"2005","journal-title":"Journal of Machine Learning Research"},{"key":"ref11","article-title":"Nonlinear regression on Riemannian manifolds and its applications to Neuro-image analysis","author":"banerjee","year":"2016","journal-title":"Med Image Comput Comput Assist Interv"},{"key":"ref40","article-title":"A Testbed for Cross-Dataset Analysis","author":"tommasi","year":"2015","journal-title":"Computer Vision ECCV Workshops Technical Report"},{"year":"2006","author":"bishop","journal-title":"Pattern Recognition and Machine Learning","key":"ref12"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1093\/biomet\/92.2.465"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1093\/biomet\/ast021"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1109\/TPAMI.2011.149","article-title":"Maximum Margin Bayesian Network Classifiers","volume":"34","author":"wohlmayr","year":"2012","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1007\/s13160-014-0141-9"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/CVPR.2013.360"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1016\/j.patcog.2009.04.017"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1007\/s11263-013-0627-y"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/TPAMI.2008.75"},{"key":"ref3","article-title":"Classification via semi-Riemannian spaces","author":"zhao","year":"2008","journal-title":"Computer Vision and Pattern Recognition"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1016\/j.patcog.2015.04.015"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/TPAMI.2007.1110"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1109\/34.473228"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1109\/AFGR.1998.670968"},{"doi-asserted-by":"publisher","key":"ref49","DOI":"10.1109\/TPAMI.2015.2392774"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1109\/CVPR.2008.4587466"},{"key":"ref46","article-title":"Directional Space-Time Oriented Gradients for 3D Visual Pattern Analysis","author":"norouznezhad","year":"2012","journal-title":"Computer Vision ECCV"},{"key":"ref45","first-page":"736","article-title":"Directional Space-Time Oriented Gradients for 3D Visual Pattern Analysis","author":"norouznezhad","year":"2012","journal-title":"Computer Vision ECCV"},{"doi-asserted-by":"publisher","key":"ref48","DOI":"10.1109\/ICCV.2015.17"},{"doi-asserted-by":"publisher","key":"ref47","DOI":"10.1109\/ICCV.2013.387"},{"doi-asserted-by":"publisher","key":"ref42","DOI":"10.1109\/CVPR.2013.368"},{"key":"ref41","article-title":"Towards Effective Codebookless Model for Image Classification","author":"wang","year":"2015","journal-title":"arXiv 1507 02385 [cs CV]"},{"key":"ref44","article-title":"Geodesic Flow Kernel for Unsupervised Domain Adaptation","author":"gong","year":"2012","journal-title":"IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref43","article-title":"Feature Evaluation of Deep Convolutional Neural Networks for Object Recognition and Detection","author":"kataoka","year":"2015","journal-title":"arXiv 1509 07627 [cs CV]"}],"event":{"name":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","start":{"date-parts":[[2016,11,30]]},"location":"Gold Coast, Australia","end":{"date-parts":[[2016,12,2]]}},"container-title":["2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7794373\/7796973\/07797063.pdf?arnumber=7797063","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T22:12:17Z","timestamp":1749852737000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7797063\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11]]},"references-count":51,"URL":"https:\/\/doi.org\/10.1109\/dicta.2016.7797063","relation":{},"subject":[],"published":{"date-parts":[[2016,11]]}}}