{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T22:20:06Z","timestamp":1743114006515,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030377335"},{"type":"electronic","value":"9783030377342"}],"license":[{"start":{"date-parts":[[2019,12,24]],"date-time":"2019-12-24T00:00:00Z","timestamp":1577145600000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-37734-2_26","type":"book-chapter","created":{"date-parts":[[2019,12,27]],"date-time":"2019-12-27T00:03:00Z","timestamp":1577404980000},"page":"316-326","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Robust RGB-D Data Registration Based on Correntropy and Bi-directional Distance"],"prefix":"10.1007","author":[{"given":"Teng","family":"Wan","sequence":"first","affiliation":[]},{"given":"Shaoyi","family":"Du","sequence":"additional","affiliation":[]},{"given":"Wenting","family":"Cui","sequence":"additional","affiliation":[]},{"given":"Qixing","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Yuying","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Zuoyong","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,12,24]]},"reference":[{"issue":"5","key":"26_CR1","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1177\/0278364911434148","volume":"31","author":"P Henry","year":"2013","unstructured":"Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: RGB-D mapping: using depth cameras for dense 3D modeling of indoor environments. Int. J. Robot. Res. 31(5), 647\u2013663 (2013)","journal-title":"Int. J. Robot. Res."},{"issue":"5","key":"26_CR2","doi-asserted-by":"publisher","first-page":"1147","DOI":"10.1109\/TRO.2015.2463671","volume":"31","author":"R Mur-Artal","year":"2015","unstructured":"Mur-Artal, R., Montiel, J.M.M., Tard\u00f3s, J.D.: ORB-SLAM: a versatile and accurate monocular SLAM system. IEEE Trans. Rob. 31(5), 1147\u20131163 (2015)","journal-title":"IEEE Trans. Rob."},{"key":"26_CR3","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.media.2017.02.005","volume":"38","author":"F Bernard","year":"2017","unstructured":"Bernard, F., et al.: Shape-aware surface reconstruction from sparse 3D point-clouds. Med. Image Anal. 38, 77\u201389 (2017)","journal-title":"Med. Image Anal."},{"issue":"2","key":"26_CR4","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"P.J. Besl","year":"1992","unstructured":"P.J. Besl, N.D. Mckay: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell., 14(2), 239\u2013256 (1992)","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"3","key":"26_CR5","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)","journal-title":"Image Vis. Comput."},{"key":"26_CR6","unstructured":"Ridene, T., Goulette, F.: Registration of fixed-and-mobile-based terrestrial Laser data sets with DSM. In: IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 375\u2013380 (2016)"},{"key":"26_CR7","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.neucom.2015.01.019","volume":"157","author":"S Du","year":"2015","unstructured":"Du, S., Liu, J., Zhang, C., Zhu, J., Li, K.: Probability iterative closest point algorithm for m-D point set registration with noise. Neurocomputing 157, 187\u2013198 (2015)","journal-title":"Neurocomputing"},{"key":"26_CR8","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.patcog.2019.03.013","volume":"93","author":"Z Wu","year":"2019","unstructured":"Wu, Z., Chen, H., Du, S., Fu, M., Zhou, N., Zheng, N.: Correntropy based scale ICP algorithm for robust point set registration. Pattern Recogn. 93, 14\u201324 (2019)","journal-title":"Pattern Recogn."},{"key":"26_CR9","doi-asserted-by":"publisher","unstructured":"Du, S., Xu, G., Zhang, S., Zhang, X., Gao, Y., Chen, B.: Robust rigid registration algorithm based on pointwise correspondence and correntropy. Pattern Recogn. Lett. (2018). https:\/\/doi.org\/10.1016\/j.patrec.2018.06.028","DOI":"10.1016\/j.patrec.2018.06.028"},{"issue":"13","key":"26_CR10","first-page":"1145","volume":"21","author":"AW Fitzgibbon","year":"2001","unstructured":"Fitzgibbon, A.W.: Robust registration of 2D and 3D point sets. Image Vis. Comput. 21(13), 1145\u20131153 (2001)","journal-title":"Image Vis. Comput."},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Benjemaa, R., Schmitt, F.: Fast global registration of 3D sampled surfaces using a multi-z-buffer technique. In: International Conference on Recent Advances in 3-D Digital Imaging and Modeling Proceedings, pp. 113\u2013123 (1997)","DOI":"10.1016\/S0262-8856(98)00115-2"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Men, H., Gebre, B., Pochiraju, K.: Color point cloud registration with 4D ICP algorithm. In: IEEE International Conference on Robotics and Automation, pp. 1511\u20131516 (2011)","DOI":"10.1109\/ICRA.2011.5980407"},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Danelljan, M., Meneghetti, G., Khan, F.S., Felsberg, M.: A probabilistic framework for color-based point set registration. In: Computer Vision and Pattern Recognition, pp. 1818\u20131826 (2016)","DOI":"10.1109\/CVPR.2016.201"},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Lai, K., Bo, L., Ren, X., Fox, D.: A large-scale hierarchical multi-view RGB-D object dataset. In: IEEE International Conference on Robotics and Automation, pp. 1817\u20131824 (2011)","DOI":"10.1109\/ICRA.2011.5980382"},{"key":"26_CR15","doi-asserted-by":"crossref","unstructured":"Sturm, J., Engelhard, N., Endres, F., Burgard, W., Cremers, D.: A benchmark for the evaluation of RGB-D SLAM systems. In: IEEE International Conference on Intelligent Robots and Systems, pp. 573\u2013580 (2012)","DOI":"10.1109\/IROS.2012.6385773"}],"container-title":["Lecture Notes in Computer Science","MultiMedia Modeling"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-37734-2_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T11:28:38Z","timestamp":1665314918000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-37734-2_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,24]]},"ISBN":["9783030377335","9783030377342"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-37734-2_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019,12,24]]},"assertion":[{"value":"24 December 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MMM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Multimedia Modeling","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Daejeon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","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":"5 January 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 January 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mmm2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mmm2020.kr\/","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":"171","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":"40","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":"23% - 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":"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":"Of the 171 submissions, 46 were accepted as poster papers; of the 49 special session paper submissions, 28 were accepted for oral presentation and 8 for poster presentation; 9 demo papers and 10 VBS papers were also accepted.","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)"}}]}}