{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T06:13:39Z","timestamp":1742969619902,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819984312"},{"type":"electronic","value":"9789819984329"}],"license":[{"start":{"date-parts":[[2023,12,24]],"date-time":"2023-12-24T00:00:00Z","timestamp":1703376000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,24]],"date-time":"2023-12-24T00:00:00Z","timestamp":1703376000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-99-8432-9_36","type":"book-chapter","created":{"date-parts":[[2023,12,23]],"date-time":"2023-12-23T08:02:17Z","timestamp":1703318537000},"page":"453-465","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Convex Hull Collaborative Representation Learning on\u00a0Grassmann Manifold with\u00a0$$L_1$$ Norm Regularization"],"prefix":"10.1007","author":[{"given":"Yao","family":"Guan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenzhu","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanmeng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,24]]},"reference":[{"key":"36_CR1","doi-asserted-by":"crossref","unstructured":"Cevikalp, H., Triggs, B.: Face recognition based on image sets. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2567\u20132573 (2010)","DOI":"10.1109\/CVPR.2010.5539965"},{"issue":"12","key":"36_CR2","doi-asserted-by":"publisher","first-page":"4481","DOI":"10.1109\/TCSVT.2019.2926165","volume":"30","author":"H Cevikalp","year":"2019","unstructured":"Cevikalp, H., Yavuz, H.S., Triggs, B.: Face recognition based on videos by using convex hulls. IEEE Trans. Circuits Syst. Video Technol. 30(12), 4481\u20134495 (2019)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"1","key":"36_CR3","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1109\/TBDATA.2021.3113084","volume":"9","author":"Z Chen","year":"2023","unstructured":"Chen, Z., Xu, T., Wu, X.J., Wang, R., Kittler, J.: Hybrid Riemannian graph-embedding metric learning for image set classification. IEEE Trans. Big Data 9(1), 75\u201392 (2023)","journal-title":"IEEE Trans. Big Data"},{"issue":"6","key":"36_CR4","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1109\/MSP.2012.2211477","volume":"29","author":"L Deng","year":"2012","unstructured":"Deng, L.: The MNIST database of handwritten digit images for machine learning research [best of the web]. IEEE Signal Process. Mag. 29(6), 141\u2013142 (2012)","journal-title":"IEEE Signal Process. Mag."},{"key":"36_CR5","doi-asserted-by":"crossref","unstructured":"Efron, B., Hastie, T., Johnstone, I., Tibshirani, R.: Least angle regression (2004)","DOI":"10.1214\/009053604000000067"},{"key":"36_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109667","volume":"254","author":"X Gao","year":"2022","unstructured":"Gao, X., Feng, Z., Wei, D., Niu, S., Zhao, H., Dong, J.: Class-specific representation based distance metric learning for image set classification. Knowl.-Based Syst. 254, 109667 (2022)","journal-title":"Knowl.-Based Syst."},{"key":"36_CR7","first-page":"2049","volume":"6","author":"A Gunawardana","year":"2005","unstructured":"Gunawardana, A., Byrne, W.: Convergence theorems for generalized alternating minimization procedures. J. Mach. Learn. Res. 6, 2049\u20132073 (2005)","journal-title":"J. Mach. Learn. Res."},{"key":"36_CR8","doi-asserted-by":"crossref","unstructured":"Harandi, M., Sanderson, C., Shen, C., Lovell, B.: Dictionary learning and sparse coding on grassmann manifolds: an extrinsic solution. In: 2013 IEEE International Conference on Computer Vision, pp. 3120\u20133127 (2013)","DOI":"10.1109\/ICCV.2013.387"},{"issue":"10","key":"36_CR9","doi-asserted-by":"publisher","first-page":"1992","DOI":"10.1109\/TPAMI.2011.283","volume":"34","author":"Y Hu","year":"2012","unstructured":"Hu, Y., Mian, A.S., Owens, R.: Face recognition using sparse approximated nearest points between image sets. IEEE Trans. Pattern Anal. Mach. Intell. 34(10), 1992\u20132004 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"36_CR10","unstructured":"Huang, G.B., Mattar, M., Berg, T., Learned-Miller, E.: Labeled faces in the wild: a database for studying face recognition in unconstrained environments. Technical report (2007)"},{"key":"36_CR11","doi-asserted-by":"crossref","unstructured":"Huang, Z., Van Gool, L.: A Riemannian network for SPD matrix learning. In: Thirty-First AAAI Conference on Artificial Intelligence (2017)","DOI":"10.1609\/aaai.v31i1.10866"},{"key":"36_CR12","doi-asserted-by":"crossref","unstructured":"Huang, Z., Wang, R., Shan, S., Chen, X.: Projection metric learning on Grassmann manifold with application to video based face recognition. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 140\u2013149 (2015)","DOI":"10.1109\/CVPR.2015.7298609"},{"key":"36_CR13","doi-asserted-by":"crossref","unstructured":"Huang, Z., Wu, J., Van Gool, L.: Building deep networks on Grassmann manifolds. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32 (2018)","DOI":"10.1609\/aaai.v32i1.11725"},{"key":"36_CR14","doi-asserted-by":"publisher","first-page":"1732","DOI":"10.1109\/TIP.2023.3251025","volume":"32","author":"Y Sun","year":"2023","unstructured":"Sun, Y., Wang, X., Peng, D., Ren, Z., Shen, X.: Hierarchical hashing learning for image set classification. IEEE Trans. Image Process. 32, 1732\u20131744 (2023)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"36_CR15","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1109\/TBDATA.2020.2982146","volume":"8","author":"R Wang","year":"2022","unstructured":"Wang, R., Wu, X.J., Chen, K.X., Kittler, J.: Multiple Riemannian manifold-valued descriptors based image set classification with multi-kernel metric learning. IEEE Trans. Big Data 8(3), 753\u2013769 (2022)","journal-title":"IEEE Trans. Big Data"},{"key":"36_CR16","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1109\/TMM.2020.2981189","volume":"23","author":"R Wang","year":"2021","unstructured":"Wang, R., Wu, X.J., Kittler, J.: Graph embedding multi-kernel metric learning for image set classification with Grassmannian manifold-valued features. IEEE Trans. Multimedia 23, 228\u2013242 (2021)","journal-title":"IEEE Trans. Multimedia"},{"issue":"5","key":"36_CR17","doi-asserted-by":"publisher","first-page":"2208","DOI":"10.1109\/TNNLS.2020.3044176","volume":"33","author":"R Wang","year":"2021","unstructured":"Wang, R., Wu, X.J., Kittler, J.: SymNet: a simple symmetric positive definite manifold deep learning method for image set classification. IEEE Trans. Neural Netw. Learn. Syst. 33(5), 2208\u20132222 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"36_CR18","doi-asserted-by":"crossref","unstructured":"Wang, R., Chen, X.: Manifold discriminant analysis (2009)","DOI":"10.1109\/CVPR.2009.5206850"},{"key":"36_CR19","doi-asserted-by":"crossref","unstructured":"Wang, R., Guo, H., Davis, L.S., Dai, Q.: Covariance discriminative learning: a natural and efficient approach to image set classification. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2496\u20132503 (2012)","DOI":"10.1109\/CVPR.2012.6247965"},{"key":"36_CR20","doi-asserted-by":"crossref","unstructured":"Wang, R., Shan, S., Chen, X., Gao, W.: Manifold-manifold distance with application to face recognition based on image set. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138 (2008)","DOI":"10.1109\/CVPR.2008.4587719"},{"issue":"9","key":"36_CR21","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.1109\/LSP.2017.2723084","volume":"24","author":"W Wang","year":"2017","unstructured":"Wang, W., Wang, R., Shan, S., Chen, X.: Prototype discriminative learning for image set classification. IEEE Signal Process. Lett. 24(9), 1318\u20131322 (2017)","journal-title":"IEEE Signal Process. Lett."},{"key":"36_CR22","doi-asserted-by":"publisher","first-page":"6471","DOI":"10.1109\/TIP.2022.3212284","volume":"31","author":"D Wei","year":"2022","unstructured":"Wei, D., Shen, X., Sun, Q., Gao, X.: Discrete metric learning for fast image set classification. IEEE Trans. Image Process. 31, 6471\u20136486 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"36_CR23","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/j.neucom.2019.12.026","volume":"385","author":"D Wei","year":"2020","unstructured":"Wei, D., Shen, X., Sun, Q., Gao, X., Yan, W.: Locality-aware group sparse coding on Grassmann manifolds for image set classification. Neurocomputing 385, 197\u2013210 (2020)","journal-title":"Neurocomputing"},{"key":"36_CR24","doi-asserted-by":"crossref","unstructured":"Yang, M., Zhu, P., Van Gool, L., Zhang, L.: Face recognition based on regularized nearest points between image sets. In: 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), pp. 1\u20137 (2013)","DOI":"10.1109\/FG.2013.6553727"},{"key":"36_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, L., Yang, M., Feng, X.: Sparse representation or collaborative representation: which helps face recognition? In: 2011 International Conference on Computer Vision, pp. 471\u2013478. IEEE (2011)","DOI":"10.1109\/ICCV.2011.6126277"},{"issue":"7","key":"36_CR26","doi-asserted-by":"publisher","first-page":"2483","DOI":"10.1007\/s00521-020-05089-x","volume":"33","author":"S Zhang","year":"2021","unstructured":"Zhang, S., Wei, D., Yan, W., Sun, Q.: Probabilistic collaborative representation on Grassmann manifold for image set classification. Neural Comput. Appl. 33(7), 2483\u20132496 (2021)","journal-title":"Neural Comput. Appl."},{"issue":"7","key":"36_CR27","doi-asserted-by":"publisher","first-page":"1120","DOI":"10.1109\/TIFS.2014.2324277","volume":"9","author":"P Zhu","year":"2014","unstructured":"Zhu, P., Zuo, W., Zhang, L., Shiu, S.C.K., Zhang, D.: Image set-based collaborative representation for face recognition. IEEE Trans. Inf. Forensics Secur. 9(7), 1120\u20131132 (2014)","journal-title":"IEEE Trans. Inf. Forensics Secur."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-8432-9_36","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T19:33:31Z","timestamp":1730921611000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-8432-9_36"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,24]]},"ISBN":["9789819984312","9789819984329"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-8432-9_36","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023,12,24]]},"assertion":[{"value":"24 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xiamen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/prcv2023.xmu.edu.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1420","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"532","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"37% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3,78","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3,69","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}