{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T13:28:20Z","timestamp":1780406900992,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","license":[{"start":{"date-parts":[[2016,3,14]],"date-time":"2016-03-14T00:00:00Z","timestamp":1457913600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2016,3,14]]},"DOI":"10.1145\/2857491.2857521","type":"proceedings-article","created":{"date-parts":[[2016,3,8]],"date-time":"2016-03-08T14:13:39Z","timestamp":1457446419000},"page":"303-306","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["Smooth pursuit detection based on multiple observers"],"prefix":"10.1145","author":[{"given":"Ioannis","family":"Agtzidis","sequence":"first","affiliation":[{"name":"Technische Universit\u00e4t M\u00fcnchen"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mikhail","family":"Startsev","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t M\u00fcnchen"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Dorr","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t M\u00fcnchen"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2016,3,14]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/304182.304187"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1167\/9.5.19"},{"key":"e_1_3_2_2_3_1","unstructured":"Chaudhuri K. and Dasgupta S. 2010. Rates of convergence for the cluster tree. In Advances in Neural Information Processing Systems 343--351.  Chaudhuri K. and Dasgupta S. 2010. Rates of convergence for the cluster tree. In Advances in Neural Information Processing Systems 343--351."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1167\/10.10.28"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168556.2168596"},{"key":"e_1_3_2_2_6_1","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"96","author":"Ester M.","year":"1996","unstructured":"Ester , M. , Kriegel , H.-P. , Sander , J. , and Xu , X. 1996 . A density-based algorithm for discovering clusters in large spatial databases with noise . In KDD Proceedings , vol. 96 , 226 -- 231 . Ester, M., Kriegel, H.-P., Sander, J., and Xu, X. 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. In KDD Proceedings, vol. 96, 226--231.","journal-title":"KDD Proceedings"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1152\/jn.2000.84.6.2725"},{"key":"e_1_3_2_2_8_1","volume-title":"Clustering Algorithms","author":"Hartigan J. A.","unstructured":"Hartigan , J. A. 1975. Clustering Algorithms , 99 th ed. John Wiley & Sons, Inc. , New York, NY, USA . Hartigan, J. A. 1975. Clustering Algorithms, 99th ed. John Wiley & Sons, Inc., New York, NY, USA.","edition":"99"},{"key":"e_1_3_2_2_9_1","volume-title":"Eye tracking: A comprehensive guide to methods and measures","author":"Holmqvist K.","unstructured":"Holmqvist , K. , Nystr\u00f6m , M. , Andersson , R. , Dewhurst , R. , Jarodzka , H. , and Van de Weijer , J. 2011. Eye tracking: A comprehensive guide to methods and measures . Oxford University Press . Holmqvist, K., Nystr\u00f6m, M., Andersson, R., Dewhurst, R., Jarodzka, H., and Van de Weijer, J. 2011. Eye tracking: A comprehensive guide to methods and measures. Oxford University Press."},{"key":"e_1_3_2_2_10_1","volume-title":"Debacl: A python package for interactive density-based clustering. arXiv preprint arXiv:1307.8136.","author":"Kent B. P.","year":"2013","unstructured":"Kent , B. P. , Rinaldo , A. , and Verstynen , T . 2013 . Debacl: A python package for interactive density-based clustering. arXiv preprint arXiv:1307.8136. Kent, B. P., Rinaldo, A., and Verstynen, T. 2013. Debacl: A python package for interactive density-based clustering. arXiv preprint arXiv:1307.8136."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2013.2258918"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Larsson L. Nystr\u00f6m M. Andersson R. and Stridh M. 2015. Detection of fixations and smooth pursuit movements in high-speed eye-tracking data. 145--152.  Larsson L. Nystr\u00f6m M. Andersson R. and Stridh M. 2015. Detection of fixations and smooth pursuit movements in high-speed eye-tracking data. 145--152.","DOI":"10.1016\/j.bspc.2014.12.008"},{"key":"e_1_3_2_2_13_1","unstructured":"Leigh R. J. and Zee D. S. 2006. The Neurology of Eye Movements fourth ed. Oxford University Press.  Leigh R. J. and Zee D. S. 2006. The Neurology of Eye Movements fourth ed. Oxford University Press."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"crossref","unstructured":"Li F. Pelz J. B. and Daly S. J. 2010. Effects of stimulus size and velocity on steady-state smooth pursuit induced by realistic images. In IS&T\/SPIE Electronic Imaging International Society for Optics and Photonics 752717--752717.  Li F. Pelz J. B. and Daly S. J. 2010. Effects of stimulus size and velocity on steady-state smooth pursuit induced by realistic images. In IS&T\/SPIE Electronic Imaging International Society for Optics and Photonics 752717--752717.","DOI":"10.1117\/12.840146"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1394281.1394287"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.08.025"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"crossref","unstructured":"Nystr\u00f6m M. Hooge I. and Holmqvist K. 2013. Postsaccadic oscillations in eye movement data recorded with pupil-based eye trackers reflect motion of the pupil inside the iris. Vision research 92 59--66.  Nystr\u00f6m M. Hooge I. and Holmqvist K. 2013. Postsaccadic oscillations in eye movement data recorded with pupil-based eye trackers reflect motion of the pupil inside the iris. Vision research 92 59--66.","DOI":"10.1016\/j.visres.2013.09.009"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00344.2010"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00415-012-6631-2"}],"event":{"name":"ETRA '16: 2016 Symposium on Eye Tracking Research and Applications","location":"Charleston South Carolina","acronym":"ETRA '16","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques","SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2857491.2857521","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2857491.2857521","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:39:09Z","timestamp":1750221549000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2857491.2857521"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,3,14]]},"references-count":19,"alternative-id":["10.1145\/2857491.2857521","10.1145\/2857491"],"URL":"https:\/\/doi.org\/10.1145\/2857491.2857521","relation":{},"subject":[],"published":{"date-parts":[[2016,3,14]]},"assertion":[{"value":"2016-03-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}