{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:20:39Z","timestamp":1742912439160,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031159336"},{"type":"electronic","value":"9783031159343"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-15934-3_40","type":"book-chapter","created":{"date-parts":[[2022,9,6]],"date-time":"2022-09-06T00:02:53Z","timestamp":1662422573000},"page":"482-494","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unsupervised Multi-view Multi-person 3D Pose Estimation Using Reprojection Error"],"prefix":"10.1007","author":[{"given":"Di\u00f3genes Wallis","family":"de Fran\u00e7a Silva","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1834-5221","authenticated-orcid":false,"given":"Jo\u00e3o Paulo Silva","family":"do Monte Lima","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2527-4548","authenticated-orcid":false,"given":"David","family":"Mac\u00eado","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6421-9747","authenticated-orcid":false,"given":"Cleber","family":"Zanchettin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8525-7133","authenticated-orcid":false,"given":"Diego Gabriel Francis","family":"Thomas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6119-1184","authenticated-orcid":false,"given":"Hideaki","family":"Uchiyama","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4685-3634","authenticated-orcid":false,"given":"Veronica","family":"Teichrieb","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,15]]},"reference":[{"key":"40_CR1","doi-asserted-by":"crossref","unstructured":"Belagiannis, V., Amin, S., Andriluka, M., Schiele, B., Navab, N., Ilic, S.: 3D pictorial structures for multiple human pose estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1669\u20131676 (2014)","DOI":"10.1109\/CVPR.2014.216"},{"issue":"10","key":"40_CR2","doi-asserted-by":"publisher","first-page":"1929","DOI":"10.1109\/TPAMI.2015.2509986","volume":"38","author":"V Belagiannis","year":"2015","unstructured":"Belagiannis, V., Amin, S., Andriluka, M., Schiele, B., Navab, N., Ilic, S.: 3D pictorial structures revisited: multiple human pose estimation. IEEE Trans. Pattern Anal. Mach. Intell. 38(10), 1929\u20131942 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"40_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1007\/978-3-319-16178-5_52","volume-title":"Computer Vision - ECCV 2014 Workshops","author":"V Belagiannis","year":"2015","unstructured":"Belagiannis, V., Wang, X., Schiele, B., Fua, P., Ilic, S., Navab, N.: Multiple human pose estimation with temporally consistent 3D pictorial structures. In: Agapito, L., Bronstein, M.M., Rother, C. (eds.) ECCV 2014. LNCS, vol. 8925, pp. 742\u2013754. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-16178-5_52"},{"key":"40_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1007\/978-3-030-58580-8_32","volume-title":"Computer Vision \u2013 ECCV 2020","author":"H Chen","year":"2020","unstructured":"Chen, H., Guo, P., Li, P., Lee, G.H., Chirikjian, G.: Multi-person 3D pose estimation in crowded scenes based on multi-view geometry. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12348, pp. 541\u2013557. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58580-8_32"},{"key":"40_CR5","doi-asserted-by":"crossref","unstructured":"Dong, J., Jiang, W., Huang, Q., Bao, H., Zhou, X.: Fast and robust multi-person 3D pose estimation from multiple views. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7792\u20137801 (2019)","DOI":"10.1109\/CVPR.2019.00798"},{"issue":"12","key":"40_CR6","doi-asserted-by":"publisher","first-page":"15573","DOI":"10.1007\/s11042-017-5133-8","volume":"77","author":"S Ershadi-Nasab","year":"2018","unstructured":"Ershadi-Nasab, S., Noury, E., Kasaei, S., Sanaei, E.: Multiple human 3D pose estimation from multiview images. Multimedia Tools Appl. 77(12), 15573\u201315601 (2018)","journal-title":"Multimedia Tools Appl."},{"key":"40_CR7","volume-title":"Multiple View Geometry in Computer Vision","author":"R Hartley","year":"2003","unstructured":"Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2003)"},{"key":"40_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1007\/978-3-030-58604-1_29","volume-title":"Computer Vision \u2013 ECCV 2020","author":"C Huang","year":"2020","unstructured":"Huang, C., et al.: End-to-end dynamic matching network for multi-view multi-person 3D pose estimation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12373, pp. 477\u2013493. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58604-1_29"},{"issue":"7","key":"40_CR9","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1109\/TPAMI.2013.248","volume":"36","author":"C Ionescu","year":"2013","unstructured":"Ionescu, C., Papava, D., Olaru, V., Sminchisescu, C.: Human3.6M: large scale datasets and predictive methods for 3D human sensing in natural environments. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1325\u20131339 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"40_CR10","doi-asserted-by":"crossref","unstructured":"Iqbal, U., Molchanov, P., Kautz, J.: Weakly-supervised 3D human pose learning via multi-view images in the wild. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5243\u20135252 (2020)","DOI":"10.1109\/CVPR42600.2020.00529"},{"key":"40_CR11","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"40_CR12","doi-asserted-by":"crossref","unstructured":"Lin, J., Lee, G.H.: Multi-view multi-person 3D pose estimation with plane sweep stereo. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11886\u201311895 (2021)","DOI":"10.1109\/CVPR46437.2021.01171"},{"key":"40_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"TY Lin","year":"2014","unstructured":"Lin, T.Y., et al.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"40_CR14","unstructured":"Nibali, A., He, Z., Morgan, S., Prendergast, L.: Numerical coordinate regression with convolutional neural networks. arXiv preprint arXiv:1801.07372 (2018)"},{"key":"40_CR15","doi-asserted-by":"crossref","unstructured":"Remelli, E., Han, S., Honari, S., Fua, P., Wang, R.: Lightweight multi-view 3D pose estimation through camera-disentangled representation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6040\u20136049 (2020)","DOI":"10.1109\/CVPR42600.2020.00608"},{"key":"40_CR16","doi-asserted-by":"crossref","unstructured":"Sun, K., Xiao, B., Liu, D., Wang, J.: Deep high-resolution representation learning for human pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5693\u20135703 (2019)","DOI":"10.1109\/CVPR.2019.00584"},{"key":"40_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1007\/978-3-030-58452-8_12","volume-title":"Computer Vision \u2013 ECCV 2020","author":"H Tu","year":"2020","unstructured":"Tu, H., Wang, C., Zeng, W.: VoxelPose: towards multi-camera 3D human pose estimation in wild environment. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12346, pp. 197\u2013212. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58452-8_12"},{"issue":"7","key":"40_CR18","doi-asserted-by":"publisher","first-page":"3797","DOI":"10.1109\/TIT.2014.2320500","volume":"60","author":"T Van Erven","year":"2014","unstructured":"Van Erven, T., Harremos, P.: R\u00e9nyi divergence and Kullback-Leibler divergence. IEEE Trans. Inf. Theory 60(7), 3797\u20133820 (2014)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"40_CR19","doi-asserted-by":"crossref","unstructured":"Xie, R., Wang, C., Wang, Y.: MetaFuse: a pre-trained fusion model for human pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13686\u201313695 (2020)","DOI":"10.1109\/CVPR42600.2020.01370"},{"key":"40_CR20","unstructured":"Zhuang, J., et al.: AdaBelief optimizer: adapting stepsizes by the belief in observed gradients. In: Advances in Neural Information Processing Systems, vol. 33, pp. 18795\u201318806 (2020)"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-15934-3_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,18]],"date-time":"2023-02-18T04:55:18Z","timestamp":1676696118000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-15934-3_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031159336","9783031159343"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-15934-3_40","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"15 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bristol","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2022\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"561","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":"255","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":"4","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":"45% - 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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}