{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T17:25:05Z","timestamp":1767893105477,"version":"3.49.0"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030584511","type":"print"},{"value":"9783030584528","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-58452-8_40","type":"book-chapter","created":{"date-parts":[[2020,11,3]],"date-time":"2020-11-03T00:34:03Z","timestamp":1604363643000},"page":"687-703","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["The Phong Surface: Efficient 3D Model Fitting Using Lifted Optimization"],"prefix":"10.1007","author":[{"given":"Jingjing","family":"Shen","sequence":"first","affiliation":[]},{"given":"Thomas J.","family":"Cashman","sequence":"additional","affiliation":[]},{"given":"Qi","family":"Ye","sequence":"additional","affiliation":[]},{"given":"Tim","family":"Hutton","sequence":"additional","affiliation":[]},{"given":"Toby","family":"Sharp","sequence":"additional","affiliation":[]},{"given":"Federica","family":"Bogo","sequence":"additional","affiliation":[]},{"given":"Andrew","family":"Fitzgibbon","sequence":"additional","affiliation":[]},{"given":"Jamie","family":"Shotton","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,3]]},"reference":[{"issue":"2","key":"40_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)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"40_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1007\/978-3-319-46454-1_34","volume-title":"Computer Vision \u2013 ECCV 2016","author":"F Bogo","year":"2016","unstructured":"Bogo, F., Kanazawa, A., Lassner, C., Gehler, P., Romero, J., Black, M.J.: Keep it SMPL: automatic estimation of 3D human pose and shape from a single image. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9909, pp. 561\u2013578. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46454-1_34"},{"key":"40_CR3","doi-asserted-by":"crossref","unstructured":"Bogo, F., Romero, J., Loper, M., Black, M.J.: FAUST: dataset and evaluation for 3D mesh registration. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3794\u20133801 (2014)","DOI":"10.1109\/CVPR.2014.491"},{"issue":"1","key":"40_CR4","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1109\/TPAMI.2012.68","volume":"35","author":"TJ Cashman","year":"2013","unstructured":"Cashman, T.J., Fitzgibbon, A.W.: What shape are dolphins? Building 3D morphable models from 2D images. IEEE Trans. Pattern Anal. Mach. Intell. 35(1), 232\u2013244 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"40_CR5","unstructured":"Chen, Y., Medioni, G.: Object modeling by registration of multiple range images. In: IEEE International Conference on Robotics and Automation, pp. 2724\u20132729 (1991)"},{"key":"40_CR6","doi-asserted-by":"crossref","unstructured":"Fitzgibbon, A.: Robust registration of 2D and 3D point sets. In: Proceedings of the British Machine Vision Conference, pp. 411\u2013420 (2001)","DOI":"10.5244\/C.15.43"},{"key":"40_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1007\/978-3-642-33783-3_18","volume-title":"Computer Vision \u2013 ECCV 2012","author":"DA Hirshberg","year":"2012","unstructured":"Hirshberg, D.A., Loper, M., Rachlin, E., Black, M.J.: Coregistration: simultaneous alignment and modeling of articulated 3D shape. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7577, pp. 242\u2013255. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33783-3_18"},{"key":"40_CR8","doi-asserted-by":"crossref","unstructured":"Khamis, S., Taylor, J., Shotton, J., Keskin, C., Izadi, S., Fitzgibbon, A.: Learning an efficient model of hand shape variation from depth images. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 2540\u20132548 (2015)","DOI":"10.1109\/CVPR.2015.7298869"},{"key":"40_CR9","doi-asserted-by":"crossref","unstructured":"Kolotouros, N., Pavlakos, G., Black, M., Daniilidis, K.: Learning to reconstruct 3D human pose and shape via model-fitting in the loop. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 2252\u20132261 (2019)","DOI":"10.1109\/ICCV.2019.00234"},{"issue":"6","key":"40_CR10","first-page":"194:1","volume":"36","author":"T Li","year":"2017","unstructured":"Li, T., Bolkart, T., Black, M.J., Li, H., Romero, J.: Learning a model of facial shape and expression from 4D scans. ACM Trans. Graph. 36(6), 194:1\u2013194:17 (2017)","journal-title":"ACM Trans. Graph."},{"key":"40_CR11","unstructured":"Loop, C.T.: Smooth subdivision surfaces based on triangles. Master\u2019s thesis, University of Utah (1987)"},{"key":"40_CR12","unstructured":"Magic Leap Inc.: Perception at Magic Leap (2019). https:\/\/sites.google.com\/view\/perceptionatmagicleap\/"},{"issue":"2","key":"40_CR13","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1137\/0111030","volume":"11","author":"DW Marquardt","year":"1963","unstructured":"Marquardt, D.W.: An algorithm for least-squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 11(2), 431\u2013441 (1963)","journal-title":"J. Soc. Ind. Appl. Math."},{"key":"40_CR14","unstructured":"Microsoft: HoloLens 2 (2019). https:\/\/blogs.microsoft.com\/blog\/2019\/02\/24\/microsoft-at-mwc-barcelona-introducing-microsoft-hololens-2"},{"issue":"4","key":"40_CR15","doi-asserted-by":"publisher","first-page":"49:1","DOI":"10.1145\/3306346.3322958","volume":"38","author":"F Mueller","year":"2019","unstructured":"Mueller, F., et al.: Real-time pose and shape reconstruction of two interacting hands with a single depth camera. ACM Trans. Graph. 38(4), 49:1\u201349:13 (2019)","journal-title":"ACM Trans. Graph."},{"key":"40_CR16","doi-asserted-by":"crossref","unstructured":"Neugebauer, P.J.: Geometrical cloning of 3D objects via simultaneous registration of multiple range images. In: International Conference on Shape Modeling and Applications, pp. 130\u2013139 (1997)","DOI":"10.1109\/SMA.1997.634890"},{"key":"40_CR17","doi-asserted-by":"crossref","unstructured":"Pavlakos, G., et al.: Expressive body capture: 3D hands, face, and body from a single image. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 10975\u201310985 (2019)","DOI":"10.1109\/CVPR.2019.01123"},{"key":"40_CR18","doi-asserted-by":"crossref","unstructured":"Pellegrini, S., Schindler, K., Nardi, D.: A generalisation of the ICP algorithm for articulated bodies. In: Proceedings of the British Machine Vision Conference, pp. 87.1\u201387.10 (2008)","DOI":"10.5244\/C.22.87"},{"issue":"6","key":"40_CR19","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1145\/360825.360839","volume":"18","author":"BT Phong","year":"1975","unstructured":"Phong, B.T.: Illumination for computer generated pictures. Commun. ACM 18(6), 311\u2013317 (1975)","journal-title":"Commun. ACM"},{"key":"40_CR20","doi-asserted-by":"crossref","unstructured":"Qian, C., Sun, X., Wei, Y., Tang, X., Sun, J.: Realtime and robust hand tracking from depth. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1106\u20131113 (2014)","DOI":"10.1109\/CVPR.2014.145"},{"issue":"4","key":"40_CR21","doi-asserted-by":"publisher","first-page":"85:1","DOI":"10.1145\/3306346.3323037","volume":"38","author":"S Rusinkiewicz","year":"2019","unstructured":"Rusinkiewicz, S.: A symmetric objective function for ICP. ACM Trans. Graph. 38(4), 85:1\u201385:7 (2019)","journal-title":"ACM Trans. Graph."},{"key":"40_CR22","doi-asserted-by":"crossref","unstructured":"Rusinkiewicz, S., Levoy, M.: Efficient variants of the ICP algorithm. In: International Conference on 3D Digital Imaging and Modeling, pp. 145\u2013152 (2001)","DOI":"10.1109\/IM.2001.924423"},{"key":"40_CR23","doi-asserted-by":"crossref","unstructured":"Sridhar, S., Oulasvirta, A., Theobalt, C.: Interactive markerless articulated hand motion tracking using RGB and depth data. In: International Conference on Computer Vision, pp. 2456\u20132463 (2013)","DOI":"10.1109\/ICCV.2013.305"},{"issue":"10","key":"40_CR24","doi-asserted-by":"publisher","first-page":"1091","DOI":"10.1109\/34.722621","volume":"20","author":"S Sullivan","year":"1998","unstructured":"Sullivan, S., Ponce, J.: Automatic model construction and pose estimation from photographs using triangular splines. IEEE Trans. Pattern Anal. Mach. Intell. 20(10), 1091\u20131097 (1998)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"40_CR25","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1111\/cgf.12700","volume":"34","author":"A Tagliasacchi","year":"2015","unstructured":"Tagliasacchi, A., Schr\u00f6der, M., Tkach, A., Bouaziz, S., Botsch, M., Pauly, M.: Robust articulated-ICP for real-time hand tracking. Comput. Graph. Forum 34(5), 101\u2013114 (2015)","journal-title":"Comput. Graph. Forum"},{"key":"40_CR26","doi-asserted-by":"crossref","unstructured":"Taylor, J., et al.: User-specific hand modeling from monocular depth sequences. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 644\u2013651 (2014)","DOI":"10.1109\/CVPR.2014.88"},{"issue":"4","key":"40_CR27","doi-asserted-by":"publisher","first-page":"143:1","DOI":"10.1145\/2897824.2925965","volume":"35","author":"J Taylor","year":"2016","unstructured":"Taylor, J., et al.: Efficient and precise interactive hand tracking through joint, continuous optimization of pose and correspondences. ACM Trans. Graph. 35(4), 143:1\u2013143:12 (2016)","journal-title":"ACM Trans. Graph."},{"issue":"6","key":"40_CR28","doi-asserted-by":"publisher","first-page":"244:1","DOI":"10.1145\/3130800.3130853","volume":"36","author":"J Taylor","year":"2017","unstructured":"Taylor, J., et al.: Articulated distance fields for ultra-fast tracking of hands interacting. ACM Trans. Graph. 36(6), 244:1\u2013244:12 (2017)","journal-title":"ACM Trans. Graph."},{"issue":"6","key":"40_CR29","doi-asserted-by":"publisher","first-page":"222:1","DOI":"10.1145\/2980179.2980226","volume":"35","author":"A Tkach","year":"2016","unstructured":"Tkach, A., Pauly, M., Tagliasacchi, A.: Sphere-meshes for real-time hand modeling and tracking. ACM Trans. Graph. 35(6), 222:1\u2013222:11 (2016)","journal-title":"ACM Trans. Graph."},{"key":"40_CR30","doi-asserted-by":"crossref","unstructured":"Wan, C., Probst, T., Gool, L.V., Yao, A.: Self-supervised 3D hand pose estimation through training by fitting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 10845\u201310854 (2019)","DOI":"10.1109\/CVPR.2019.01111"},{"key":"40_CR31","doi-asserted-by":"crossref","unstructured":"Xiang, D., Joo, H., Sheikh, Y.: Monocular total capture: posing face, body, and hands in the wild. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 10957\u201310966 (2018)","DOI":"10.1109\/CVPR.2019.01122"},{"key":"40_CR32","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/j.cag.2013.10.023","volume":"38","author":"J Zheng","year":"2014","unstructured":"Zheng, J., Zeng, M., Cheng, X., Liu, X.: SCAPE-based human performance reconstruction. Comput. Graph. 38, 191\u2013198 (2014)","journal-title":"Comput. Graph."},{"key":"40_CR33","doi-asserted-by":"crossref","unstructured":"Zuffi, S., Kanazawa, A., Black, M.J.: Lions and tigers and bears: capturing non-rigid, 3D, articulated shape from images. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3955\u20133963 (2018)","DOI":"10.1109\/CVPR.2018.00416"},{"key":"40_CR34","doi-asserted-by":"crossref","unstructured":"Zuffi, S., Kanazawa, A., Jacobs, D.W., Black, M.J.: 3D menagerie: modeling the 3D shape and pose of animals. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 5524\u20135532 (2017)","DOI":"10.1109\/CVPR.2017.586"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58452-8_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:19:14Z","timestamp":1730593154000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58452-8_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030584511","9783030584528"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58452-8_40","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"3 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Glasgow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","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":"23 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2020.eu\/","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":"OpenReview","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5025","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":"1360","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":"27% - 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":"7","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":"The conference was held virtually due to the COVID-19 pandemic.","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)"}}]}}