{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T21:16:55Z","timestamp":1726003015378},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030043742"},{"type":"electronic","value":"9783030043759"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","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":[[2018]]},"DOI":"10.1007\/978-3-030-04375-9_27","type":"book-chapter","created":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T21:24:53Z","timestamp":1544217893000},"page":"320-333","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Learning 3DMM Deformation Coefficients for Rendering Realistic Expression Images"],"prefix":"10.1007","author":[{"given":"Claudio","family":"Ferrari","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefano","family":"Berretti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pietro","family":"Pala","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alberto","family":"Del Bimbo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,12,8]]},"reference":[{"key":"27_CR1","doi-asserted-by":"crossref","unstructured":"Amberg, B., Romdhani, S., Vetter, T.: Optimal step nonrigid ICP algorithms for surface registration. In: IEEE International Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, pp. 1\u20138, June 2007","DOI":"10.1109\/CVPR.2007.383165"},{"key":"27_CR2","doi-asserted-by":"crossref","unstructured":"Blanz, V., Vetter, T.: A morphable model for the synthesis of 3D faces. In: ACM Conference on Computer Graphics and Interactive Techniques (1999)","DOI":"10.1145\/311535.311556"},{"issue":"9","key":"27_CR3","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1109\/TPAMI.2003.1227983","volume":"25","author":"V Blanz","year":"2003","unstructured":"Blanz, V., Vetter, T.: Face recognition based on fitting a 3D morphable model. IEEE Trans. Pattern Anal. Mach. Intell. 25(9), 1063\u20131074 (2003)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"27_CR4","doi-asserted-by":"publisher","unstructured":"Booth, J., Antonakos, E., Ploumpis, S., Trigeorgis, G., Panagakis, Y., Zafeiriou, S.: 3D face morphable models \u201cin-the-wild\u201d. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5464\u20135473, July 2017. https:\/\/doi.org\/10.1109\/CVPR.2017.580","DOI":"10.1109\/CVPR.2017.580"},{"key":"27_CR5","doi-asserted-by":"crossref","unstructured":"Booth, J., Roussos, A., Zafeiriou, S., Ponniahand, A., Dunaway, D.: A 3D morphable model learnt from 10,000 faces. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 5543\u20135552 (2016)","DOI":"10.1109\/CVPR.2016.598"},{"key":"27_CR6","doi-asserted-by":"crossref","unstructured":"Cosker, D., Krumhuber, E., Hilton, A.: Perception of linear and nonlinear motion properties using a FACS validated 3D facial model. In: ACM Applied Perception in Graphics and Vision (2010)","DOI":"10.1145\/1836248.1836268"},{"key":"27_CR7","doi-asserted-by":"crossref","unstructured":"Cosker, D., Krumhuber, E., Hilton, A.: A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling. In: International Conference on Computer Vision (2011)","DOI":"10.1109\/ICCV.2011.6126510"},{"key":"27_CR8","doi-asserted-by":"crossref","unstructured":"Cosker, D., Krumhuber, E., Hilton, A.: Perceived emotionality of linear and non-linear AUs synthesised using a 3D dynamic morphable facial model. In: Proceedings of the Facial Analysis and Animation, FAA 2015, p. 7:1. ACM (2015)","DOI":"10.1145\/2813852.2813859"},{"key":"27_CR9","doi-asserted-by":"publisher","unstructured":"Dou, P., Shah, S.K., Kakadiaris, I.A.: End-to-end 3D face reconstruction with deep neural networks. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1503\u20131512, July 2017. https:\/\/doi.org\/10.1109\/CVPR.2017.164","DOI":"10.1109\/CVPR.2017.164"},{"issue":"4","key":"27_CR10","first-page":"384","volume":"48","author":"P Ekman","year":"1992","unstructured":"Ekman, P.: Facial expression and emotion. Am. Anthropol. 48(4), 384\u2013392 (1992)","journal-title":"Am. Anthropol."},{"key":"27_CR11","doi-asserted-by":"crossref","unstructured":"Ekman, P., Friesen, W.: Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto, CA (1978)","DOI":"10.1037\/t27734-000"},{"issue":"12","key":"27_CR12","doi-asserted-by":"publisher","first-page":"2666","DOI":"10.1109\/TMM.2017.2707341","volume":"19","author":"C Ferrari","year":"2017","unstructured":"Ferrari, C., Lisanti, G., Berretti, S., Del Bimbo, A.: A dictionary learning-based 3D morphable shape model. IEEE Trans. Multimedia 19(12), 2666\u20132679 (2017). https:\/\/doi.org\/10.1109\/TMM.2017.2707341","journal-title":"IEEE Trans. Multimedia"},{"key":"27_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/978-3-319-46484-8_5","volume-title":"Computer Vision \u2013 ECCV 2016","author":"G Hu","year":"2016","unstructured":"Hu, G., et al.: Face recognition using a unified 3D morphable model. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9912, pp. 73\u201389. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46484-8_5"},{"key":"27_CR14","unstructured":"Huang, G.B., Ramesh, M., Berg, T., Learned-Miller, E.: Labeled faces in the wild: a database for studying face recognition in unconstrained environments. Technical report 07-49, University of Massachusetts, Amherst, October 2007"},{"key":"27_CR15","doi-asserted-by":"publisher","unstructured":"Huang, Y., Khan, S.M.: DyadGAN: generating facial expressions in dyadic interactions. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 2259\u20132266, July 2017. https:\/\/doi.org\/10.1109\/CVPRW.2017.280","DOI":"10.1109\/CVPRW.2017.280"},{"key":"27_CR16","unstructured":"Huber, P., Kopp, P., R\u00e4tsch, M., Christmas, W.J., Kittler, J.: 3D face tracking and texture fusion in the wild. CoRR abs\/1605.06764 (2016). http:\/\/arxiv.org\/abs\/1605.06764"},{"key":"27_CR17","doi-asserted-by":"crossref","unstructured":"Kazemi, V., Sullivan, J.: One millisecond face alignment with an ensemble of regression trees. In: IEEE Conference on Computer Vision and Pattern Recognition (2014)","DOI":"10.1109\/CVPR.2014.241"},{"key":"27_CR18","doi-asserted-by":"crossref","unstructured":"Lucey, P., Cohn, J.F., Kanade, T., Saragih, J., Ambadar, Z., Matthews, I.: The extended Cohn-Kanade dataset (CK+): a complete dataset for action unit and emotion-specified expression. In: IEEE Conference on Computer Vision and Pattern Recognition-Workshops (2010)","DOI":"10.1109\/CVPRW.2010.5543262"},{"key":"27_CR19","doi-asserted-by":"crossref","unstructured":"Mairal, J., Bach, F., Ponce, J., Sapiro, G.: Online dictionary learning for sparse coding. In: International Conference on Machine Learning (2009)","DOI":"10.1145\/1553374.1553463"},{"key":"27_CR20","doi-asserted-by":"crossref","unstructured":"Masi, I., Ferrari, C., Del Bimbo, A., Medioni, G.: Pose independent face recognition by localizing local binary patterns via deformation components. In: International Conference on Pattern Recognition (2014)","DOI":"10.1109\/ICPR.2014.766"},{"key":"27_CR21","doi-asserted-by":"crossref","unstructured":"Patel, A., Smith, W.A.P.: 3D morphable face models revisited. In: IEEE Conference on Computer Vision and Pattern Recognition (2009)","DOI":"10.1109\/CVPR.2009.5206522"},{"key":"27_CR22","doi-asserted-by":"crossref","unstructured":"Paysan, P., Knothe, R., Amberg, B., Romdhani, S., Vetter, T.: A 3D face model for pose and illumination invariant face recognition. In: IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pp. 296\u2013301 (2009)","DOI":"10.1109\/AVSS.2009.58"},{"key":"27_CR23","unstructured":"Qiao, F., Yao, N., Jiao, Z., Li, Z., Chen, H., Wang, H.: Geometry-contrastive generative adversarial network for facial expression synthesis. CoRR abs\/1802.01822 (2018). http:\/\/arxiv.org\/abs\/1802.01822"},{"key":"27_CR24","doi-asserted-by":"crossref","unstructured":"Ramanathan, S., Kassim, A., Venkatesh, Y.V., Wah, W.S.: Human facial expression recognition using a 3D morphable model. In: International Conference on Image Processing (2006)","DOI":"10.1109\/ICIP.2006.312417"},{"key":"27_CR25","doi-asserted-by":"crossref","unstructured":"Romdhani, S., Vetter, T.: Estimating 3D shape and texture using pixel intensity, edges, specular highlights, texture constraints and a prior. In: IEEE Conference on Computer Vision and Pattern Recognition (2005)","DOI":"10.1109\/CVPR.2005.145"},{"key":"27_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/978-3-540-89991-4_6","volume-title":"Biometrics and Identity Management","author":"A Savran","year":"2008","unstructured":"Savran, A., et al.: Bosphorus database for 3D face analysis. In: Schouten, B., Juul, N.C., Drygajlo, A., Tistarelli, M. (eds.) BioID 2008. LNCS, vol. 5372, pp. 47\u201356. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-89991-4_6"},{"key":"27_CR27","doi-asserted-by":"crossref","unstructured":"Tran, A.T., Hassner, T., Masi, I., Medioni, G.: Regressing robust and discriminative 3D morphable models with a very deep neural network. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5163\u20135172, July 2017","DOI":"10.1109\/CVPR.2017.163"},{"key":"27_CR28","series-title":"Lecture Notes in Computational Vision and Biomechanics","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/978-94-007-0726-9_2","volume-title":"Topics in Medical Image Processing and Computational Vision","author":"H Ujir","year":"2013","unstructured":"Ujir, H., Spann, M.: Facial expression recognition using FAPs-based 3DMMM. In: Tavares, J., Natal Jorge, R. (eds.) Topics in Medical Image Processing and Computational Vision. LNCVB, vol. 8, pp. 33\u201347. Springer, Dordrecht (2013). https:\/\/doi.org\/10.1007\/978-94-007-0726-9_2"},{"key":"27_CR29","doi-asserted-by":"crossref","unstructured":"Yi, D., Lei, Z., Li, S.Z.: Towards pose robust face recognition. In: IEEE Conference on Computer Vision and Pattern Recognition (2013)","DOI":"10.1109\/CVPR.2013.454"},{"key":"27_CR30","unstructured":"Yin, L., Wei, X., Sun, Y., Wang, J., Rosato, M.: A 3D facial expression database for facial behavior research. In: IEEE International Conference on Automatic Face and Gesture Recognition (2006)"},{"key":"27_CR31","doi-asserted-by":"crossref","unstructured":"Zhu, X., Lei, Z., Liu, X., Shi, H., Li, S.Z.: Face alignment across large poses: a 3D solution. In: IEEE Conference on Computer Vision and Pattern Recognition (2016)","DOI":"10.1109\/CVPR.2016.23"}],"container-title":["Lecture Notes in Computer Science","Smart Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-04375-9_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,6]],"date-time":"2019-11-06T21:33:50Z","timestamp":1573076030000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-04375-9_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030043742","9783030043759"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-04375-9_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"ICSM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Smart Multimedia","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toulon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","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":"24 August 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icsm2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.smartmultimedia.org\/","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"}},{"value":"PaperPlaza by Papercept Inc.","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"100","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"20","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"12","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"20% - 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"}},{"value":"3.0","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"4.0","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"The \"Other\" papers and talks were under the Special Sessions which were reviewed by the special session chairs separately.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}