{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:35:54Z","timestamp":1742913354662,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":32,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811610912"},{"type":"electronic","value":"9789811610929"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-16-1092-9_17","type":"book-chapter","created":{"date-parts":[[2021,3,27]],"date-time":"2021-03-27T16:02:26Z","timestamp":1616860946000},"page":"196-207","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dual Gradient Feature Pair Based Face Recognition for Aging and Pose Changes"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5513-9929","authenticated-orcid":false,"given":"V. Betcy Thanga","family":"Shoba","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"I. Shatheesh","family":"Sam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,3,28]]},"reference":[{"key":"17_CR1","unstructured":"Huang, G.B., Ramesh, M., Berg, T.: Learned-miller E Labeled Faces in the Wild\u202f: A Database for Studying Face Recognition in Unconstrained Environments, pp. 1\u201311"},{"issue":"8","key":"17_CR2","doi-asserted-by":"publisher","first-page":"1991","DOI":"10.1007\/s00521-015-1843-x","volume":"26","author":"W Jadoon","year":"2015","unstructured":"Jadoon, W., Zhang, L., Zhang, Y.: Extended collaborative neighbor representation for robust single-sample face recognition. Neural Comput. Appl. 26(8), 1991\u20132000 (2015). https:\/\/doi.org\/10.1007\/s00521-015-1843-x","journal-title":"Neural Comput. Appl."},{"key":"17_CR3","first-page":"2117","volume":"36","author":"Q Cheng","year":"2014","unstructured":"Cheng, Q., Zhou, H., Cheng, J., Li, H.: A Minimax Framework for Classification with Applications to Images and High Dimensional Data. 36, 2117\u20132130 (2014)","journal-title":"A Minimax Framework for Classification with Applications to Images and High Dimensional Data."},{"key":"17_CR4","unstructured":"Ding, Z., Suh, S., Han, J., et al.: Discriminative Low-Rank Metric Learning for Face Recognition, pp. 1\u20136 (2015)"},{"key":"17_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.12.029","author":"J Zhu","year":"2016","unstructured":"Zhu, J., Zheng, W., Lu, F.: Illumination invariant single face image recognition under Heterogeneous Lighting Condition. Pattern Recogn. (2016). https:\/\/doi.org\/10.1016\/j.patcog.2016.12.029","journal-title":"Pattern Recogn."},{"key":"17_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TPAMI.2015.2462338","volume":"8828","author":"C Ding","year":"2015","unstructured":"Ding, C., Member, S., Choi, J., Member, S.: Multi-Directional Multi-Level Dual-Cross. 8828, 1\u20135 (2015). https:\/\/doi.org\/10.1109\/TPAMI.2015.2462338","journal-title":"Multi-Directional Multi-Level Dual-Cross."},{"key":"17_CR7","doi-asserted-by":"crossref","unstructured":"Riggan, B.S., Reale, C., Member, S.: Coupled Auto-Associative Neural Networks for Heterogeneous Face Recognition. 3 (2015)","DOI":"10.1109\/ACCESS.2015.2479620"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Ding, Y., Qin, Z., Li, B., Yuan, X.: Facial Expression Recognition From Image Sequence Based on LBP and Taylor Expansion (2017)","DOI":"10.1109\/ACCESS.2017.2737821"},{"key":"17_CR9","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1109\/TPAMI.2016.2535218","volume":"39","author":"J Yang","year":"2017","unstructured":"Yang, J., Luo, L., Qian, J., et al.: Nuclear norm based matrix regression with applications to face recognition with occlusion and illumination changes. IEEE Trans. Pattern Anal. Mach. Intell. 39, 156\u2013171 (2017). https:\/\/doi.org\/10.1109\/TPAMI.2016.2535218","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"17_CR10","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1016\/j.patrec.2010.11.021","volume":"32","author":"CS Il","year":"2011","unstructured":"Il, C.S., Choi, C.H., Kwak, N.: Face recognition based on 2D images under illumination and pose variations. Pattern Recogn. Lett. 32, 561\u2013571 (2011). https:\/\/doi.org\/10.1016\/j.patrec.2010.11.021","journal-title":"Pattern Recogn. Lett."},{"key":"17_CR11","doi-asserted-by":"crossref","unstructured":"Turk M, Pentland A E i g e d c e s for Recognition. 3","DOI":"10.1162\/jocn.1991.3.1.71"},{"key":"17_CR12","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1109\/34.598228","volume":"19","author":"PN Belhumeur","year":"1997","unstructured":"Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19, 711\u2013720 (1997). https:\/\/doi.org\/10.1109\/34.598228","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"17_CR13","first-page":"467","volume":"11","author":"H Wechsler","year":"2002","unstructured":"Wechsler, H.: Gabor Feature Based Classification Using the Enhanced Fisher Linear Discriminant Model for Face Recognition. 11, 467\u2013476 (2002)","journal-title":"Gabor Feature Based Classification Using the Enhanced Fisher Linear Discriminant Model for Face Recognition."},{"key":"17_CR14","unstructured":"Zou J, Ji Q, Member S, Nagy G A Comparative Study of Local Matching Approach for Face Recognition. 1\u201329"},{"key":"17_CR15","doi-asserted-by":"crossref","unstructured":"Liao, S., Yi, D., Lei, Z., et al.: Heterogeneous Face Recognition from Local Structures of Normalized Appearance, pp. 209\u2013218 (2009)","DOI":"10.1007\/978-3-642-01793-3_22"},{"key":"17_CR16","doi-asserted-by":"crossref","unstructured":"Chai, Z., Mendez-vazquez, H., He, R., Sun, Z.: Semantic Pixel Sets Based Local Binary Patterns for Face Recognition, pp. 639\u2013651 (2013)","DOI":"10.1007\/978-3-642-37444-9_50"},{"key":"17_CR17","doi-asserted-by":"publisher","first-page":"784","DOI":"10.4218\/etrij.10.1510.0132","volume":"32","author":"T Jabid","year":"2010","unstructured":"Jabid, T., Kabir, H., Chae, O.: Robust Facial Expression Recognition Based on Local Directional Pattern. 32, 784\u2013794 (2010). https:\/\/doi.org\/10.4218\/etrij.10.1510.0132","journal-title":"Robust Facial Expression Recognition Based on Local Directional Pattern."},{"key":"17_CR18","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2603535","author":"S Chakraborty","year":"2016","unstructured":"Chakraborty, S., Member, S., Singh, S.K., Member, S.: Local gradient hexa pattern: a descriptor for face recognition and retrieval. (2016). https:\/\/doi.org\/10.1109\/TCSVT.2016.2603535","journal-title":"Local gradient hexa pattern: a descriptor for face recognition and retrieval."},{"key":"17_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.01.023","author":"X Jing","year":"2016","unstructured":"Jing, X., Wu, F., Zhu, X., et al.: Multi-spectral low-rank structured dictionary learning for face recognition. Pattern Recogn. (2016). https:\/\/doi.org\/10.1016\/j.patcog.2016.01.023","journal-title":"Pattern Recogn."},{"key":"17_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2017.07.006","author":"W Ou","year":"2017","unstructured":"Ou, W., Luan, X., Gou, J., et al.: PT US CR. Pattern Recogn. Lett. (2017). https:\/\/doi.org\/10.1016\/j.patrec.2017.07.006","journal-title":"Pattern Recogn. Lett."},{"key":"17_CR21","doi-asserted-by":"crossref","unstructured":"Nagpal, S., Singh, M., Singh, R., Member S Regularized Deep Learning for Face Recognition With Weight Variations 3 (2016)","DOI":"10.1109\/ACCESS.2015.2510865"},{"key":"17_CR22","unstructured":"Yin, X., Member XL Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition, pp. 1\u201312"},{"key":"17_CR23","doi-asserted-by":"publisher","unstructured":"Moeini, A., Moeini, H.: Real-World and Rapid Face Recognition towards Pose and Expression Variations via Feature Library Matrix. 6013 (2015). https:\/\/doi.org\/https:\/\/doi.org\/10.1109\/TIFS.2015.2393553","DOI":"10.1109\/TIFS.2015.2393553"},{"key":"17_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TPAMI.2015.2408359","volume":"8828","author":"J Lu","year":"2015","unstructured":"Lu, J., Liong, V.E., Zhou, X., Zhou, J.: Learning compact binary face descriptor for face recognition. 8828, 1\u20136 (2015). https:\/\/doi.org\/10.1109\/TPAMI.2015.2408359","journal-title":"Learning compact binary face descriptor for face recognition."},{"key":"17_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2001.990517","author":"P Viola","year":"2001","unstructured":"Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. (2001). https:\/\/doi.org\/10.1109\/CVPR.2001.990517","journal-title":"Rapid object detection using a boosted cascade of simple features."},{"key":"17_CR26","unstructured":"Ricanek Jr., K., Tesafaye, T.: MORPH: A longitudinal image Age-progression, of normal adult. In: Proceedings of the 7th Int Conf Autom Face Gesture Recognit 0\u20134 (2006)"},{"key":"17_CR27","unstructured":"Face and Gestrure Recognition Research Network(FGNET) Database: https:\/\/yanwifu.github.io\/FG_NET_data\/FGNET.zip"},{"key":"17_CR28","unstructured":"Yale Faces Database. https:\/\/vision.ucsd.edu\/content\/yale-face-database"},{"issue":"7","key":"17_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-019-1335-0","volume":"43","author":"KK Kamarajugadda","year":"2019","unstructured":"Kamarajugadda, K.K., Polipalli, T.R.: Extract features from periocular region to identify the age using machine learning algorithms. J. Med. Syst. 43(7), 1\u20135 (2019). https:\/\/doi.org\/10.1007\/s10916-019-1335-0","journal-title":"J. Med. Syst."},{"key":"17_CR30","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.jvcir.2018.02.004","volume":"53","author":"L Wang","year":"2018","unstructured":"Wang, L., Cheng, H., Liu, Z.: A set-to-set nearest neighbor approach for robust and efficient face recognition with image sets \u2606, \u2606\u2606. J. Vis. Commun. Image Represent. 53, 13\u201319 (2018). https:\/\/doi.org\/10.1016\/j.jvcir.2018.02.004","journal-title":"J. Vis. Commun. Image Represent."},{"key":"17_CR31","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.image.2017.03.012","volume":"55","author":"W Zhu","year":"2017","unstructured":"Zhu, W., Yan, Y., Peng, Y.: Pair of projections based on sparse consistence with applications to efficient face recognition. Signal Process. Image Commun. 55, 32\u201340 (2017). https:\/\/doi.org\/10.1016\/j.image.2017.03.012","journal-title":"Signal Process. Image Commun."},{"key":"17_CR32","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.jocs.2018.08.005","volume":"28","author":"SA Khan","year":"2018","unstructured":"Khan, S.A., Ishtiaq, M., Nazir, M., Shaheen, M.: Face recognition under varying expressions and illumination using particle swarm optimization. J. Comput. Sci. 28, 94\u2013100 (2018). https:\/\/doi.org\/10.1016\/j.jocs.2018.08.005","journal-title":"J. Comput. Sci."}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-1092-9_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T19:52:49Z","timestamp":1619293969000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-1092-9_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811610912","9789811610929"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-1092-9_17","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"28 March 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Prayagraj","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cvip2020.iiita.ac.in","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"352","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":"134","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":"38% - 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","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":"4","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic the conference was partially held in a virtual mode.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}