{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T20:01:48Z","timestamp":1743105708074,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030134686"},{"type":"electronic","value":"9783030134693"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-13469-3_69","type":"book-chapter","created":{"date-parts":[[2019,3,2]],"date-time":"2019-03-02T13:03:53Z","timestamp":1551531833000},"page":"594-601","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["3D Face Recognition with Reconstructed Faces from a Collection of 2D Images"],"prefix":"10.1007","author":[{"given":"Jo\u00e3o Baptista Cardia","family":"Neto","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aparecido Nilceu","family":"Marana","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,3,3]]},"reference":[{"issue":"2","key":"69_CR1","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"PJ Besl","year":"1992","unstructured":"Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239\u2013256 (1992). https:\/\/doi.org\/10.1109\/34.121791","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"69_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/978-3-319-75193-1_17","volume-title":"Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications","author":"JB Cardia Neto","year":"2018","unstructured":"Cardia Neto, J.B., Marana, A.N.: Utilizing deep learning and 3DLBP for 3D face recognition. In: Mendoza, M., Velast\u00edn, S. (eds.) CIARP 2017. LNCS, vol. 10657, pp. 135\u2013142. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-75193-1_17"},{"issue":"3","key":"69_CR3","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/j.imavis.2004.05.007","volume":"23","author":"D Chetverikov","year":"2005","unstructured":"Chetverikov, D., Stepanov, D., Krsek, P.: Robust Euclidean alignment of 3D point sets: the trimmed iterative closest point algorithm. Image Vis. Comput. 23(3), 299\u2013309 (2005). https:\/\/doi.org\/10.1016\/j.imavis.2004.05.007. http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0262885604001179","journal-title":"Image Vis. Comput."},{"key":"69_CR4","doi-asserted-by":"publisher","unstructured":"Huang, Y., Wang, Y., Tan, T.: Combining statistics of geometrical and correlative features for 3D face recognition. In: Proceedings of the British Machine Vision Conference, pp. 90.1\u201390.10. BMVA Press (2006). https:\/\/doi.org\/10.5244\/C.20.90","DOI":"10.5244\/C.20.90"},{"issue":"4","key":"69_CR5","doi-asserted-by":"publisher","first-page":"640","DOI":"10.1109\/TPAMI.2007.1017","volume":"29","author":"IA Kakadiaris","year":"2007","unstructured":"Kakadiaris, I.A., et al.: Three-dimensional face recognition in the presence of facial expressions: an annotated deformable model approach. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 640\u2013649 (2007). https:\/\/doi.org\/10.1109\/TPAMI.2007.1017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"69_CR6","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/978-3-319-25958-1_8","volume-title":"Advances in Face Detection and Facial Image Analysis","author":"E Learned-Miller","year":"2016","unstructured":"Learned-Miller, E., Huang, G.B., RoyChowdhury, A., Li, H., Hua, G.: Labeled faces in the wild: a survey. In: Kawulok, M., Celebi, M.E., Smolka, B. (eds.) Advances in Face Detection and Facial Image Analysis, pp. 189\u2013248. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-25958-1_8"},{"key":"69_CR7","doi-asserted-by":"publisher","unstructured":"Li, B., Mian, A., Liu, W., Krishna, A.: Using kinect for face recognition under varying poses, expressions, illumination and disguise. In: 2013 IEEE Workshop on Applications of Computer Vision (WACV), pp. 186\u2013192 (2013). https:\/\/doi.org\/10.1109\/WACV.2013.6475017","DOI":"10.1109\/WACV.2013.6475017"},{"key":"69_CR8","unstructured":"Liu, J., Deng, Y., Bai, T., Huang, C.: Targeting ultimate accuracy: face recognition via deep embedding. CoRR abs\/1506.07310 (2015). http:\/\/arxiv.org\/abs\/1506.07310"},{"key":"69_CR9","series-title":"Studies in Computational Intelligence","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1007\/978-3-319-76081-0_31","volume-title":"Modern Approaches for Intelligent Information and Database Systems","author":"V Nguyen","year":"2018","unstructured":"Nguyen, V., Do, T., Nguyen, V.-T., Ngo, T.D., Duong, D.A.: How to choose deep face models for surveillance system? In: Sieminski, A., Kozierkiewicz, A., Nunez, M., Ha, Q.T. (eds.) Modern Approaches for Intelligent Information and Database Systems. SCI, vol. 769, pp. 367\u2013376. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-76081-0_31"},{"key":"69_CR10","doi-asserted-by":"crossref","unstructured":"Parkhi, O.M., Vedaldi, A., Zisserman, A., et al.: Deep face recognition. In: BMVC, vol. 1, p. 6 (2015)","DOI":"10.5244\/C.29.41"},{"key":"69_CR11","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1109\/MSECP.2003.1193209","volume":"1","author":"S Prabhakar","year":"2003","unstructured":"Prabhakar, S., Pankanti, S., Jain, A.: Biometric recognition: security and privacy concerns. IEEE Secur. Priv. 1, 33\u201342 (2003). https:\/\/doi.org\/10.1109\/MSECP.2003.1193209","journal-title":"IEEE Secur. Priv."},{"key":"69_CR12","volume-title":"Numerical Recipes 3rd Edition: The Art of Scientific Computing","author":"WH Press","year":"2007","unstructured":"Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes 3rd Edition: The Art of Scientific Computing, 3rd edn. Cambridge University Press, New York (2007)","edition":"3"},{"key":"69_CR13","doi-asserted-by":"crossref","unstructured":"Roth, J., Tong, Y., Liu, X.: Unconstrained 3D face reconstruction. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2015","DOI":"10.1109\/CVPR.2015.7298876"},{"issue":"8","key":"69_CR14","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1021\/ac60214a047","volume":"36","author":"A Savitzky","year":"1964","unstructured":"Savitzky, A., Golay, M.J.E.: Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 36(8), 1627\u20131639 (1964). https:\/\/doi.org\/10.1021\/ac60214a047","journal-title":"Anal. Chem."},{"issue":"4","key":"69_CR15","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1109\/MSP.2011.941097","volume":"28","author":"RW Schafer","year":"2011","unstructured":"Schafer, R.W.: What is a savitzky-golay filter? [lecture notes]. IEEE Signal Process. Mag. 28(4), 111\u2013117 (2011). https:\/\/doi.org\/10.1109\/MSP.2011.941097","journal-title":"IEEE Signal Process. Mag."},{"key":"69_CR16","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: FaceNet: a unified embedding for face recognition and clustering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2015","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"69_CR17","doi-asserted-by":"crossref","unstructured":"Sun, Y., Wang, X., Tang, X.: Deeply learned face representations are sparse, selective, and robust. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2015","DOI":"10.1109\/CVPR.2015.7298907"},{"key":"69_CR18","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.neucom.2018.01.079","volume":"287","author":"G Wen","year":"2018","unstructured":"Wen, G., Chen, H., Cai, D., He, X.: Improving face recognition with domain adaptation. Neurocomputing 287, 45\u201351 (2018). https:\/\/doi.org\/10.1016\/j.neucom.2018.01.079. http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0925231218301127","journal-title":"Neurocomputing"},{"key":"69_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1007\/978-3-319-46478-7_31","volume-title":"Computer Vision \u2013 ECCV 2016","author":"Y Wen","year":"2016","unstructured":"Wen, Y., Zhang, K., Li, Z., Qiao, Y.: A discriminative feature learning approach for deep face recognition. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9911, pp. 499\u2013515. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46478-7_31"}],"container-title":["Lecture Notes in Computer Science","Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-13469-3_69","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,2]],"date-time":"2023-03-02T01:14:04Z","timestamp":1677719644000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-13469-3_69"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030134686","9783030134693"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-13469-3_69","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"3 March 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CIARP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Iberoamerican Congress on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Madrid","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 November 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ciarp2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/atvs.ii.uam.es\/ciarp2018\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"187","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":"112","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":"60% - 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":"2,94","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":"5","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":"This content has been made available to all.","name":"free","label":"Free to read"}]}}