{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T10:47:44Z","timestamp":1761648464334,"version":"3.37.3"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2017,7,15]],"date-time":"2017-07-15T00:00:00Z","timestamp":1500076800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61471261","61179067"],"award-info":[{"award-number":["61471261","61179067"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["U1333110"],"award-info":[{"award-number":["U1333110"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Spanish Government","award":["TIN2013-47276-C6-1-R"],"award-info":[{"award-number":["TIN2013-47276-C6-1-R"]}]},{"name":"Catalan Government","award":["2014-SGR-1232"],"award-info":[{"award-number":["2014-SGR-1232"]}]},{"name":"Secretaria d\u2019Universitats i Recerca del Departament d\u2019Empresa i Coneixement de la Generalitat de Catalunya"},{"DOI":"10.13039\/501100004895","name":"European Social Fund","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004895","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2018,5]]},"DOI":"10.1007\/s00521-017-3148-8","type":"journal-article","created":{"date-parts":[[2017,7,15]],"date-time":"2017-07-15T00:55:55Z","timestamp":1500080155000},"page":"371-387","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A group-based signal filtering approach for trajectory abstraction and restoration"],"prefix":"10.1007","volume":"29","author":[{"given":"Yuejun","family":"Guo","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8243-6670","authenticated-orcid":false,"given":"Qing","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Xiaoxiao","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Hao","family":"Wei","sequence":"additional","affiliation":[]},{"given":"Hongjuan","family":"Bu","sequence":"additional","affiliation":[]},{"given":"Mateu","family":"Sbert","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,7,15]]},"reference":[{"key":"3148_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47578-3","volume-title":"Outlier analysis","author":"CC Aggarwal","year":"2017","unstructured":"Aggarwal CC (2017) Outlier analysis. Springer, Berlin. doi: 10.1007\/978-3-319-47578-3"},{"key":"3148_CR2","doi-asserted-by":"crossref","DOI":"10.1201\/b15410","volume-title":"Data clustering: algorithms and applications","author":"CC Aggarwal","year":"2013","unstructured":"Aggarwal CC, Reddy CK (2013) Data clustering: algorithms and applications. Chapman and Hall\/CRC, London"},{"key":"3148_CR3","unstructured":"Aircraft dataset. https:\/\/c3.nasa.gov\/dashlink\/resources\/132\/ . Accessed 22 June 2017"},{"issue":"12","key":"3148_CR4","doi-asserted-by":"publisher","first-page":"5949","DOI":"10.1016\/j.amc.2010.12.110","volume":"217","author":"G Allasia","year":"2011","unstructured":"Allasia G, Besenghi R, Cavoretto R, Rossi AD (2011) Scattered and track data interpolation using an efficient strip searching procedure. Appl Math Comput 217(12):5949\u20135966. doi: 10.1016\/j.amc.2010.12.110","journal-title":"Appl Math Comput"},{"key":"3148_CR5","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/978-3-642-03456-5_16","volume-title":"Efficient algorithms: essays dedicated to Kurt Mehlhorn on the occasion of his 60th birthday","author":"H Alt","year":"2009","unstructured":"Alt H (2009) The computational geometry of comparing shapes. In: Albers S, Alt H, N\u00e4her S (eds) Efficient algorithms: essays dedicated to Kurt Mehlhorn on the occasion of his 60th birthday. Springer, Berlin, pp 235\u2013248. doi: 10.1007\/978-3-642-03456-5_16"},{"issue":"11","key":"3148_CR6","doi-asserted-by":"publisher","first-page":"1555","DOI":"10.1109\/TCSVT.2008.2005603","volume":"18","author":"N Anjum","year":"2008","unstructured":"Anjum N, Cavallaro A (2008) Multifeature object trajectory clustering for video analysis. IEEE Trans Circuits Syst Video Technol 18(11):1555\u20131564. doi: 10.1109\/TCSVT.2008.2005603","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"3148_CR7","doi-asserted-by":"publisher","unstructured":"Ankerst M, Breunig MM, Kriegel HP, Sander J (1999) Optics: ordering points to identify the clustering structure. In: Proceedings of the 1999 ACM SIGMOD international conference on management of data, SIGMOD \u201999, pp 49\u201360. ACM, New York. DOI: 10.1145\/304181.304187","DOI":"10.1145\/304181.304187"},{"key":"3148_CR8","unstructured":"Best track dataset. http:\/\/weather.unisys.com\/hurricane\/atlantic\/ . Accessed 22 June 2017"},{"key":"3148_CR9","doi-asserted-by":"publisher","unstructured":"Buades A, Coll B, Morel JM (2005) A non-local algorithm for image denoising. In: IEEE computer society conference on computer vision and pattern recognition, CVPR \u201905, vol 2, pp 60\u201365. IEEE Computer Society, Washington, DC, USA. DOI: 10.1109\/CVPR.2005.38","DOI":"10.1109\/CVPR.2005.38"},{"issue":"4","key":"3148_CR10","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1109\/TCSVT.2011.2125550","volume":"21","author":"S Calderara","year":"2011","unstructured":"Calderara S, Prati A, Cucchiara R (2011) Mixtures of von mises distributions for people trajectory shape analysis. IEEE Trans Circuits Syst Video Technol 21(4):457\u2013471. doi: 10.1109\/TCSVT.2011.2125550","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"3","key":"3148_CR11","doi-asserted-by":"publisher","first-page":"15:1","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V Chandola","year":"2009","unstructured":"Chandola V, Banerjee A, Kumar V (2009) Anomaly detection: a survey. ACM Comput Surv 41(3):15:1\u201315:58. doi: 10.1145\/1541880.1541882","journal-title":"ACM Comput Surv"},{"key":"3148_CR12","series-title":"Lecture notes of the institute for computer sciences, social informatics and telecommunications engineering","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/978-3-642-30973-1_6","volume-title":"Mobile and ubiquitous systems: computing, networking, and services. MobiQuitous 2011","author":"C Chen","year":"2012","unstructured":"Chen C, Zhang D, Castro PS, Li N, Sun L, Li S (2012) Real-time detection of anomalous taxi trajectories from GPS traces. In: Puiatti A, Gu I (eds) Mobile and ubiquitous systems: computing, networking, and services. MobiQuitous 2011, vol 104. Lecture notes of the institute for computer sciences, social informatics and telecommunications engineering. Springer, Berlin, pp 63\u201374. doi: 10.1007\/978-3-642-30973-1_6"},{"key":"3148_CR13","doi-asserted-by":"publisher","unstructured":"Chen W, Chang SF (2000) Motion trajectory matching of video objects. In: Storage and retrieval for media databases, vol 3972, pp 544\u2013553. The International Society for Optical Engineering. DOI: 10.1117\/12.373587","DOI":"10.1117\/12.373587"},{"issue":"1","key":"3148_CR14","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1109\/JSTSP.2012.2234081","volume":"7","author":"DA Clifton","year":"2013","unstructured":"Clifton DA, Clifton L, Hugueny S, Wong D, Tarassenko L (2013) An extreme function theory for novelty detection. IEEE J Select Top Signal Process 7(1):28\u201337. doi: 10.1109\/JSTSP.2012.2234081","journal-title":"IEEE J Select Top Signal Process"},{"issue":"8","key":"3148_CR15","doi-asserted-by":"publisher","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","volume":"16","author":"K Dabov","year":"2007","unstructured":"Dabov K, Foi A, Katkovnik V, Egiazarian K (2007) Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Trans Image Process 16(8):2080\u20132095. doi: 10.1109\/TIP.2007.901238","journal-title":"IEEE Trans Image Process"},{"issue":"2","key":"3148_CR16","doi-asserted-by":"publisher","first-page":"1542","DOI":"10.14778\/1454159.1454226","volume":"1","author":"H Ding","year":"2008","unstructured":"Ding H, Trajcevski G, Scheuermann P, Wang X, Keogh E (2008) Querying and mining of time series data: experimental comparison of representations and distance measures. Proce VLDB Endow 1(2):1542\u20131552. doi: 10.14778\/1454159.1454226","journal-title":"Proce VLDB Endow"},{"key":"3148_CR17","unstructured":"Edinburgh dataset. http:\/\/homepages.inf.ed.ac.uk\/rbf\/FORUMTRACKING\/ . Accessed 22 June 2017"},{"key":"3148_CR18","unstructured":"Ester M, Kriegel HP, Sander J, Xu X (1996) A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of the second international conference on knowledge discovery and data mining, KDD\u201996, pp 226\u2013231. AAAI Press"},{"issue":"2","key":"3148_CR19","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1145\/191843.191925","volume":"23","author":"C Faloutsos","year":"1994","unstructured":"Faloutsos C, Ranganathan M, Manolopoulos Y (1994) Fast subsequence matching in time-series databases. SIGMOD Rec 23(2):419\u2013429. doi: 10.1145\/191843.191925","journal-title":"SIGMOD Rec"},{"issue":"6","key":"3148_CR20","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler MA, Bolles RC (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24(6):381\u2013395. doi: 10.1145\/358669.358692","journal-title":"Commun ACM"},{"issue":"4","key":"3148_CR21","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1109\/TITS.2011.2160628","volume":"12","author":"M Gariel","year":"2011","unstructured":"Gariel M, Srivastava AN, Feron E (2011) Trajectory clustering and an application to airspace monitoring. IEEE Trans Intell Transp Syst 12(4):1511\u20131524. doi: 10.1109\/TITS.2011.2160628","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"3148_CR22","series-title":"Lecture notes in computer science","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1007\/978-3-319-26535-3_48","volume-title":"Neural information processing","author":"Y Guo","year":"2015","unstructured":"Guo Y, Xu Q, Liang S, Fan Y, Sbert M (2015) Xaibo: an extension of AIB for trajectory clustering with outlier. In: Arik S, Huang T, Lai WK, Liu Q (eds) Neural information processing, vol 9490. Lecture notes in computer science. Springer, Berlin, pp 423\u2013431. doi: 10.1007\/978-3-319-26535-3_48"},{"key":"3148_CR23","unstructured":"Guo Y, Xu Q, Yang Y, Liang S, Liu Y, Sbert M (2014) Anomaly detection based on trajectory analysis using kernel density estimation and information bottleneck techniques. Technical report 108, University of Girona. http:\/\/gilab.udg.edu\/wp-content\/uploads\/publications\/IIiA-15-01-RR.pdf"},{"key":"3148_CR24","unstructured":"Hazan A, Lacaille J, Madani K (2012) Extreme value statistics for vibration spectra outlier detection. In: International conference on condition monitoring and machinery failure prevention technologies, p 1. Londres, UK"},{"issue":"2","key":"3148_CR25","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1111\/1467-9868.00071","volume":"59","author":"IM Johnstone","year":"1997","unstructured":"Johnstone IM, Silverman BW (1997) Wavelet threshold estimators for data with correlated noise. J R Stat Soc Ser B (Methodol) 59(2):319\u2013351. doi: 10.1111\/1467-9868.00071","journal-title":"J R Stat Soc Ser B (Methodol)"},{"key":"3148_CR26","doi-asserted-by":"publisher","unstructured":"Jr, R.A., Forster CHQ (2012) Analysis of aircraft trajectories using fourier descriptors and kernel density estimation. In: 15th international IEEE conference on intelligent transportation systems, pp 1441\u20131446. IEEE, Anchorage, Alsaka, USA. DOI: 10.1109\/ITSC.2012.6338863","DOI":"10.1109\/ITSC.2012.6338863"},{"issue":"1","key":"3148_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0003-2670(00)83259-6","volume":"241","author":"J Kragten","year":"1990","unstructured":"Kragten J (1990) Least-squares polynomial curve-fitting for calibration purposes (statcal-calibra). Anal Chim Acta 241(1):1\u201313. doi: 10.1016\/S0003-2670(00)83259-6","journal-title":"Anal Chim Acta"},{"issue":"6","key":"3148_CR28","doi-asserted-by":"publisher","first-page":"1158","DOI":"10.1109\/TPAMI.2013.172","volume":"36","author":"R Laxhammar","year":"2014","unstructured":"Laxhammar R, Falkman G (2014) Online learning and sequential anomaly detection in trajectories. IEEE Trans Pattern Anal Mach Intell 36(6):1158\u20131173. doi: 10.1109\/TPAMI.2013.172","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"3148_CR29","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1109\/18.61115","volume":"37","author":"J Lin","year":"1991","unstructured":"Lin J (1991) Divergence measures based on the Shannon entropy. IEEE Trans Inf Theory 37(1):145\u2013151. doi: 10.1109\/18.61115","journal-title":"IEEE Trans Inf Theory"},{"issue":"2","key":"3148_CR30","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TIT.1982.1056489","volume":"28","author":"S Lloyd","year":"1982","unstructured":"Lloyd S (1982) Least squares quantization in PCM. IEEE Trans Inf Theory 28(2):129\u2013137. doi: 10.1109\/TIT.1982.1056489","journal-title":"IEEE Trans Inf Theory"},{"key":"3148_CR31","series-title":"Lecture notes in computer science","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1007\/978-3-319-26555-1_51","volume-title":"Neural information processing","author":"X Luo","year":"2015","unstructured":"Luo X, Xu Q, Guo Y, Wei H, Lv Y (2015) Trajectory abstracting with group-based signal denoising. In: Arik S, Huang T, Lai WK, Liu Q (eds) Neural information processing, vol 9491. Lecture notes in computer science. Springer, Berlin, pp 452\u2013461. doi: 10.1007\/978-3-319-26555-1_51"},{"key":"3148_CR32","doi-asserted-by":"publisher","unstructured":"May R, Hanrahan P, Keim DA, Shneiderman B, Card S (2010) The state of visual analytics: views on what visual analytics is and where it is going. In: IEEE symposium on visual analytics science and technology, pp 257\u2013259. IEEE. DOI: 10.1109\/VAST.2010.5649078","DOI":"10.1109\/VAST.2010.5649078"},{"issue":"8","key":"3148_CR33","doi-asserted-by":"publisher","first-page":"1114","DOI":"10.1109\/TCSVT.2008.927109","volume":"18","author":"BT Morris","year":"2008","unstructured":"Morris BT, Trivedi MM (2008) A survey of vision-based trajectory learning and analysis for surveillance. IEEE Trans Circuits Syst Video Technol 18(8):1114\u20131127. doi: 10.1109\/TCSVT.2008.927109","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"11","key":"3148_CR34","doi-asserted-by":"publisher","first-page":"2287","DOI":"10.1109\/TPAMI.2011.64","volume":"33","author":"BT Morris","year":"2011","unstructured":"Morris BT, Trivedi MM (2011) Trajectory learning for activity understanding: unsupervised, multilevel, and long-term adaptive approach. IEEE Trans Pattern Anal Mach Intell 33(11):2287\u20132301. doi: 10.1109\/TPAMI.2011.64","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"3148_CR35","doi-asserted-by":"publisher","first-page":"041,113","DOI":"10.1117\/1.JEI.22.4.041113","volume":"22","author":"BT Morris","year":"2013","unstructured":"Morris BT, Trivedi MM (2013) Understanding vehicular traffic behavior from video: a survey of unsupervised approaches. J Electron Imaging 22(4):041,113\u2013041,113. doi: 10.1117\/1.JEI.22.4.041113","journal-title":"J Electron Imaging"},{"issue":"4","key":"3148_CR36","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1109\/TMM.2011.2122247","volume":"13","author":"S Ntalampiras","year":"2011","unstructured":"Ntalampiras S, Potamitis I, Fakotakis N (2011) Probabilistic novelty detection for acoustic surveillance under real-world conditions. IEEE Trans Multimed 13(4):713\u2013719. doi: 10.1109\/TMM.2011.2122247","journal-title":"IEEE Trans Multimed"},{"key":"3148_CR37","unstructured":"Omni dataset. http:\/\/cvrr.ucsd.edu\/bmorris\/datasets\/dataset_trajectory_analysis.html . Accessed 22 June 2017"},{"issue":"11","key":"3148_CR38","doi-asserted-by":"publisher","first-page":"1544","DOI":"10.1109\/TCSVT.2008.2005599","volume":"18","author":"C Piciarelli","year":"2008","unstructured":"Piciarelli C, Micheloni C, Foresti GL (2008) Trajectory-based anomalous event detection. IEEE Trans Circuits Syst Video Technol 18(11):1544\u20131554. doi: 10.1109\/TCSVT.2008.2005599","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"3148_CR39","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.sigpro.2013.12.026","volume":"99","author":"MA Pimentel","year":"2014","unstructured":"Pimentel MA, Clifton DA, Clifton L, Tarassenko L (2014) A review of novelty detection. Signal Process 99:215\u2013249. doi: 10.1016\/j.sigpro.2013.12.026","journal-title":"Signal Process"},{"key":"3148_CR40","unstructured":"Recorded video dataset. http:\/\/www-users.cs.umn.edu\/~aleks\/inclof\/ . Accessed 22 June 2017"},{"issue":"6191","key":"3148_CR41","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"A Rodriguez","year":"2014","unstructured":"Rodriguez A, Laio A (2014) Clustering by fast search and find of density peaks. Science 344(6191):1492\u20131496. doi: 10.1126\/science.1242072","journal-title":"Science"},{"key":"3148_CR42","doi-asserted-by":"publisher","unstructured":"Sahouria E, Zakhor A (1997) Motion indexing of video. In: International conference on image processing, vol\u00a02, pp 526\u2013529. IEEE, Santa Barbara, CA, USA. DOI: 10.1109\/ICIP.1997.638824","DOI":"10.1109\/ICIP.1997.638824"},{"key":"3148_CR43","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511801181","volume-title":"An introduction to numerical analysis","author":"E S\u00fcli","year":"2003","unstructured":"S\u00fcli E, Mayers DF (2003) An introduction to numerical analysis. Cambridge University Press, Cambridge"},{"key":"3148_CR44","unstructured":"Synthetic dataset. http:\/\/avires.dimi.uniud.it\/papers\/trclust\/ . Accessed 22 June 2017"},{"key":"3148_CR45","unstructured":"Vlachos M, Lin J, Keogh E, Gunopulos D (2003) A wavelet-based anytime algorithm for k-means clustering of time series. In: Proceedings of workshop on clustering high dimensionality data and its applications, Citeseer, pp 23\u201330"},{"key":"3148_CR46","unstructured":"Wang W, Yang J, Muntz R (1997) Sting: A statistical information grid approach to spatial data mining. In: Proceedings of the 23rd international conference on very large data bases, VLDB \u201997, vol 97. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, pp 186\u2013195"},{"key":"3148_CR47","doi-asserted-by":"publisher","unstructured":"Zhang T, Ramakrishnan R, Livny M (1996) Birch: An efficient data clustering method for very large databases. In: ACM SIGMOD international conference on management of data, SIGMOD \u201996, pp 103\u2013114. ACM, New York, NY, USA. DOI: 10.1145\/235968.233324","DOI":"10.1145\/235968.233324"},{"issue":"3","key":"3148_CR48","doi-asserted-by":"publisher","first-page":"29:1","DOI":"10.1145\/2743025","volume":"6","author":"Y Zheng","year":"2015","unstructured":"Zheng Y (2015) Trajectory data mining: an overview. ACM Trans Intell Syst Technol 6(3):29:1\u201329:41. doi: 10.1145\/2743025","journal-title":"ACM Trans Intell Syst Technol"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-017-3148-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3148-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3148-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,30]],"date-time":"2019-09-30T06:12:55Z","timestamp":1569823975000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-017-3148-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7,15]]},"references-count":48,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2018,5]]}},"alternative-id":["3148"],"URL":"https:\/\/doi.org\/10.1007\/s00521-017-3148-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2017,7,15]]}}}