{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T09:36:46Z","timestamp":1768297006872,"version":"3.49.0"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030934194","type":"print"},{"value":"9783030934200","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-93420-0_18","type":"book-chapter","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T00:46:22Z","timestamp":1642034782000},"page":"184-193","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Skelibras: A Large 2D Skeleton Dataset of\u00a0Dynamic Brazilian Signs"],"prefix":"10.1007","author":[{"given":"Lucas","family":"Amaral","sequence":"first","affiliation":[]},{"given":"Victor","family":"Ferraz","sequence":"additional","affiliation":[]},{"given":"Tiago","family":"Vieira","sequence":"additional","affiliation":[]},{"given":"Thales","family":"Vieira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,13]]},"reference":[{"key":"18_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"930","DOI":"10.1007\/978-3-030-13469-3_107","volume-title":"Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications","author":"L Amaral","year":"2019","unstructured":"Amaral, L., J\u00fanior, G.L.N., Vieira, T., Vieira, T.: Evaluating deep models for dynamic brazilian sign language recognition. In: Vera-Rodriguez, R., Fierrez, J., Morales, A. (eds.) CIARP 2018. LNCS, vol. 11401, pp. 930\u2013937. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-13469-3_107"},{"key":"18_CR2","unstructured":"Amos, B., Ludwiczuk, B., Satyanarayanan, M.: Openface: a general-purpose face recognition library with mobile applications. Tech. rep., CMU-CS-16-118, CMU Sch. Comput. Sci. (2016)"},{"issue":"3","key":"18_CR3","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1007\/s10993-012-9245-8","volume":"11","author":"SC Batterbury","year":"2012","unstructured":"Batterbury, S.C.: Language justice for sign language peoples: the un convention on the rights of persons with disabilities. Lang. Policy 11(3), 253\u2013272 (2012)","journal-title":"Lang. Policy"},{"key":"18_CR4","doi-asserted-by":"crossref","unstructured":"Camgoz, N.C., Hadfield, S., Koller, O., Ney, H., Bowden, R.: Neural sign language translation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7784\u20137793 (2018)","DOI":"10.1109\/CVPR.2018.00812"},{"key":"18_CR5","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","volume":"43","author":"Z Cao","year":"2019","unstructured":"Cao, Z., Hidalgo Martinez, G., Simon, T., Wei, S., Sheikh, Y.A.: Openpose: realtime multi-person 2d pose estimation using part affinity fields. IEEE Trans. Pattern Anal. Mach. Intell. 43, 172\u2013186 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"18_CR6","doi-asserted-by":"crossref","unstructured":"Cardenas, E.J.E., Ch\u00e1vez, G.C.: Finger spelling recognition from depth data using direction cosines and histogram of cumulative magnitudes. In: SIBGRAPI, pp. 173\u2013179. IEEE (2015)","DOI":"10.1109\/SIBGRAPI.2015.49"},{"key":"18_CR7","unstructured":"Das, M., Kyte, R., Fisiy, C.F.: Inclusion Matters: The Foundation for Shared Prosperity. World Bank, Bretton Woods (2013)"},{"issue":"5","key":"18_CR8","doi-asserted-by":"publisher","first-page":"977","DOI":"10.1109\/72.623199","volume":"8","author":"SS Fels","year":"1997","unstructured":"Fels, S.S., Hinton, G.E.: Glove-talk ii - a neural-network interface which maps gestures to parallel formant speech synthesizer controls. IEEE Trans. Neural Netw. 8(5), 977\u2013984 (1997). https:\/\/doi.org\/10.1109\/72.623199","journal-title":"IEEE Trans. Neural Netw."},{"issue":"5","key":"18_CR9","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.1109\/TCYB.2013.2265378","volume":"43","author":"J Han","year":"2013","unstructured":"Han, J., Shao, L., Xu, D., Shotton, J.: Enhanced computer vision with microsoft kinect sensor: a review. IEEE Trans. Cybern. 43(5), 1318\u20131334 (2013)","journal-title":"IEEE Trans. Cybern."},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Herath, S., Harandi, M., Porikli, F.: Going deeper into action recognition: a survey (2017)","DOI":"10.1016\/j.imavis.2017.01.010"},{"key":"18_CR11","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/RBME.2020.3019769","volume":"14","author":"K Kudrinko","year":"2021","unstructured":"Kudrinko, K., Flavin, E., Zhu, X., Li, Q.: Wearable sensor-based sign language recognition: a comprehensive review. IEEE Rev. Biomed. Eng. 14, 82\u201397 (2021). https:\/\/doi.org\/10.1109\/RBME.2020.3019769","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"18_CR12","volume-title":"3D User Interfaces: Theory and Practice","author":"JJ LaViola","year":"2017","unstructured":"LaViola, J.J., Kruijff, E., McMahan, R.P., Bowman, D., Poupyrev, I.P.: 3D User Interfaces: Theory and Practice. Addison-Wesley Professional, Boston (2017)"},{"key":"18_CR13","doi-asserted-by":"crossref","unstructured":"Pizzolato, E.B., dos Santos Anjo, M., Pedroso, G.C.: Automatic recognition of finger spelling for libras based on a two-layer architecture. In: Proceedings of the 2010 ACM Symposium on Applied Computing, pp. 969\u2013973. ACM (2010)","DOI":"10.1145\/1774088.1774290"},{"issue":"1","key":"18_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-020-18073-9","volume":"11","author":"M Popel","year":"2020","unstructured":"Popel, M., et al.: Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals. Nature Commun. 11(1), 1\u201315 (2020)","journal-title":"Nature Commun."},{"key":"18_CR15","unstructured":"Nijmegen: Max Planck Institute for Psycholinguistics, T.L.A.: Elan (version 6.0) [computer software] (2020). https:\/\/archive.mpi.nl\/tla\/elan"},{"key":"18_CR16","unstructured":"Quadros, R.M.D., Schmitt, D., Lohn, J.T., Leite, T.d.A.: Corpus de libras. http:\/\/corpuslibras.ufsc.br\/"},{"key":"18_CR17","doi-asserted-by":"publisher","unstructured":"Rastgoo, R., Kiani, K., Escalera, S.: Sign language recognition: a deep survey. Expert Syst. Appl. 164, 113794 (2021). https:\/\/doi.org\/10.1016\/j.eswa.2020.113794, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S095741742030614X","DOI":"10.1016\/j.eswa.2020.113794"},{"key":"18_CR18","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, pp. 815\u2013823 (2015)","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"18_CR19","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"18_CR20","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1007\/978-981-15-4409-5_89","volume-title":"Advances in Computer, Communication and Computational Sciences","author":"Z Sun","year":"2021","unstructured":"Sun, Z.: A survey on dynamic sign language recognition. In: Bhatia, S.K., Tiwari, S., Ruidan, S., Trivedi, M.C., Mishra, K.K. (eds.) Advances in Computer, Communication and Computational Sciences. AISC, vol. 1158, pp. 1015\u20131022. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-15-4409-5_89"},{"key":"18_CR21","doi-asserted-by":"publisher","unstructured":"Xia, Z., et al.: Vision-based hand gesture recognition for human-robot collaboration: a survey. In: 2019 5th International Conference on Control, Automation and Robotics (ICCAR), pp. 198\u2013205 (2019). https:\/\/doi.org\/10.1109\/ICCAR.2019.8813509","DOI":"10.1109\/ICCAR.2019.8813509"}],"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\/978-3-030-93420-0_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T01:02:44Z","timestamp":1768266164000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-93420-0_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030934194","9783030934200"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-93420-0_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"13 January 2022","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":"Porto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 May 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 May 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ciarp2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ciarp2020.org\/","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":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"82","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":"45","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":"55% - 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","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":"2","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":"No","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)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}