{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,13]],"date-time":"2026-11-13T01:37:48Z","timestamp":1794533868938,"version":"4.9.1"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319488806","type":"print"},{"value":"9783319488813","type":"electronic"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"vor","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":[[2016]]},"DOI":"10.1007\/978-3-319-48881-3_51","type":"book-chapter","created":{"date-parts":[[2016,11,2]],"date-time":"2016-11-02T09:19:08Z","timestamp":1478078348000},"page":"728-742","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Anomaly Detection and Activity Perception Using Covariance Descriptor for Trajectories"],"prefix":"10.1007","author":[{"given":"Hamza","family":"Ergezer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kemal","family":"Leblebicio\u011flu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2016,11,3]]},"reference":[{"issue":"10","key":"51_CR1","doi-asserted-by":"publisher","first-page":"1713","DOI":"10.1109\/TPAMI.2008.75","volume":"30","author":"O Tuzel","year":"2008","unstructured":"Tuzel, O., Porikli, F., Meer, P.: Pedestrian detection via classification on riemannian manifolds. IEEE Trans. Pattern Anal. Mach. Intell. 30(10), 1713\u20131727 (2008)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"51_CR2","unstructured":"Porikli, F., Tuzel, O., Meer, P.: Covariance tracking using model update based on lie algebra. In: CVPR (2006)"},{"issue":"6","key":"51_CR3","doi-asserted-by":"publisher","first-page":"2479","DOI":"10.1109\/TIP.2013.2252622","volume":"22","author":"K Guo","year":"2013","unstructured":"Guo, K., Ishwar, P., Konrad, J.: Action recognition from video using feature covariance matrices. IEEE Trans. Image Process. 22(6), 2479\u20132494 (2013)","journal-title":"IEEE Trans. Image Process."},{"key":"51_CR4","unstructured":"Bilinski, P., Bremond, F.: Video covariance matrix logarithm for human action recognition in videos. In: IJCAI 2015-24th International Joint Conference on Artificial Intelligence (2015)"},{"key":"51_CR5","doi-asserted-by":"crossref","unstructured":"Wang, H., Yi, Y., Wu, J.: Human action recognition with trajectory based covariance descriptor in unconstrained videos. In: Proceedings of the 23rd ACM International Conference on Multimedia 2015, pp. 1175\u20131178 (2015)","DOI":"10.1145\/2733373.2806310"},{"issue":"4","key":"51_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1167\/13.4.11","volume":"13","author":"E Erdem","year":"2013","unstructured":"Erdem, E., Erdem, A.: Visual saliency estimation by nonlinearly integrating features using region covariances. J. Vis. 13(4), 1\u201320 (2013)","journal-title":"J. Vis."},{"issue":"7","key":"51_CR7","doi-asserted-by":"publisher","first-page":"1912","DOI":"10.1109\/TIP.2007.898960","volume":"16","author":"FI Bashir","year":"2007","unstructured":"Bashir, F.I., Khokhar, A.A., Schonfeld, D.: Object trajectory-based activity classification and recognition using hidden markov models. IEEE Trans. Image Process. 16(7), 1912\u20131919 (2007)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"51_CR8","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1007\/s11263-011-0459-6","volume":"95","author":"X Wang","year":"2011","unstructured":"Wang, X., Ma, K.T., Ng, G.W., Grimson, W.E.L.: Trajectory analysis and semantic region modeling using nonparametric hierarchical bayesian models. Int. J. Comput. Vis. 95(3), 287\u2013312 (2011)","journal-title":"Int. J. Comput. Vis."},{"issue":"11","key":"51_CR9","doi-asserted-by":"publisher","first-page":"2287","DOI":"10.1109\/TPAMI.2011.64","volume":"33","author":"BT Morris","year":"2011","unstructured":"Morris, B.T., Trivedi, M.M.: Trajectory learning for activity understanding: unsupervised, multilevel, and long-term adaptive approach. IEEE Trans. Pattern Anal. Mach. Intell. 33(11), 2287\u20132301 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"51_CR10","doi-asserted-by":"crossref","unstructured":"Keogh, E., Pazzani, M.: Scaling up dynamic time warping for datamining applications. In: International Conference on Knowledge Discovery and Data Mining (2000)","DOI":"10.1145\/347090.347153"},{"issue":"4","key":"51_CR11","doi-asserted-by":"publisher","first-page":"1168","DOI":"10.1109\/TIP.2006.891352","volume":"16","author":"W Hu","year":"2007","unstructured":"Hu, W., Xie, D., Fu, Z., Zeng, W., Maybank, S.: Semantic-based surveillance video retrieval. IEEE Trans. Image Process. 16(4), 1168\u20131181 (2007)","journal-title":"IEEE Trans. Image Process."},{"key":"51_CR12","doi-asserted-by":"crossref","unstructured":"Buzan, D., Sclaroff, S., Kollios, G.: Extraction and clustering of motion trajectories in video. In: Proceedings IEEE International Conference on Pattern Recognition, August 2004","DOI":"10.1109\/ICPR.2004.1334287"},{"issue":"11","key":"51_CR13","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, G.: Trajectory-based anomalous event detection. IEEE Trans. Circ. Syst. Video Technol. 18(11), 1544\u20131554 (2008)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"51_CR14","doi-asserted-by":"crossref","unstructured":"Atev, S., Masoud, O., Papanikolopoulos, N.: Learning traffic patterns at intersections by spectral clustering of motion trajectories. In: IEEE Conference Intelligence Robots and Systems (2006)","DOI":"10.1109\/IROS.2006.282362"},{"key":"51_CR15","doi-asserted-by":"crossref","unstructured":"Morris, B., Trivedi., M.: Learning trajectory patterns by clustering: experimental studies and comparative evaluation. In: CVPR (2009)","DOI":"10.1109\/CVPR.2009.5206559"},{"key":"51_CR16","unstructured":"Zhang, Z., Huang, K., Tan, T.: Comparison of similarity measures for trajectory clustering in outdoor surveillance scenes. In: ICPR (2006)"},{"key":"51_CR17","doi-asserted-by":"crossref","unstructured":"Mahadevan, V., Li, W., Bhalodia, V., Vasconcelos, N.: Anomaly detection in crowded scenes. In: CVPR (2010)","DOI":"10.1109\/CVPR.2010.5539872"},{"issue":"1","key":"51_CR18","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/TPAMI.2013.111","volume":"36","author":"W Li","year":"2014","unstructured":"Li, W., Mahadevan, V., Vasconcelos, N.: Anomaly detection and localization in crowded scenes. IEEE Trans. Pattern Anal. Mach. Intell. 36(1), 18\u201332 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"51_CR19","doi-asserted-by":"crossref","unstructured":"Wu, S., Moore, B.E., Shah, M.: Chaotic invariants of lagrangian particle trajectories for anomaly detection in crowded scenes. In: CVPR (2010)","DOI":"10.1109\/CVPR.2010.5539882"},{"issue":"6","key":"51_CR20","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.: Online learning and sequential anomaly detection in trajectories. IEEE Trans. Pattern Anal. Mach. Intell. 36(6), 1158\u20131173 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"51_CR21","unstructured":"Keogh, E., Lin, J., Fu, A.: Hot sax: efficiently finding the most unusual time series subsequence. In: ICDM (2005)"},{"issue":"3","key":"51_CR22","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1109\/TPAMI.2008.87","volume":"31","author":"X Wang","year":"2009","unstructured":"Wang, X., Ma, X., Grimson, W.E.L.: Unsupervised activity perception in crowded and complicated scenes using hierarchical bayesian models. IEEE Trans. Pattern Anal. Mach. Intell. 31(3), 539\u2013555 (2009)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"51_CR23","doi-asserted-by":"crossref","unstructured":"Hospedales, T., Gong, S., Xiang, T.: A markov clustering topic model for mining behaviour in video. In: IEEE 12th International Conference on Computer Vision, pp. 1165\u20131172 (2009)","DOI":"10.1109\/ICCV.2009.5459342"},{"key":"51_CR24","doi-asserted-by":"crossref","unstructured":"Kuettel, D., Breitenstein, M.D., Gool, L.V., Ferrari, V.: What\u2019s going on? discovering spatio-temporal dependencies in dynamic scenes. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1951\u20131958 (2010)","DOI":"10.1109\/CVPR.2010.5539869"},{"issue":"1","key":"51_CR25","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1214\/13-AOAS701","volume":"8","author":"J Su","year":"2014","unstructured":"Su, J., Kurtek, S., Klassen, E., Srivastava, A.: Statistical analysis of trajectories on riemannian manifolds: bird migration, hurricane tracking and video surveillance. Ann. Appl. Stat. 8(1), 530\u2013552 (2014)","journal-title":"Ann. Appl. Stat."},{"key":"51_CR26","doi-asserted-by":"crossref","unstructured":"Su, J., Srivastava, A., de Souza, F.D.M., Sarkar, S.: Rate-invariant analysis of trajectories on riemannian manifolds with application in visual speech recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 620\u2013627 (2014)","DOI":"10.1109\/CVPR.2014.86"},{"issue":"2","key":"51_CR27","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1002\/mrm.20965","volume":"56","author":"V Arsigny","year":"2006","unstructured":"Arsigny, V., Fillard, P., Pennec, X., Ayache, N.: Log-euclidean metrics for fast and simple calculus on diffusion tensors. Magn. Reson. Med. 56(2), 411\u2013421 (2006)","journal-title":"Magn. Reson. Med."},{"key":"51_CR28","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1007\/978-3-662-05296-9_31","volume-title":"Geodesy-The Challenge of the 3rd Millennium","author":"Wolfgang F\u00f6rstner","year":"2003","unstructured":"Forstner, W., Moonen, B.: A metric for covariance matrices. In: Grafarend, E.W., Krumm, F.W., Schwarze, V.S. (eds.) Geodesy-The Challenge of the 3rd Millennium. Springer, Heidelberg (2003)"},{"issue":"7","key":"51_CR29","doi-asserted-by":"publisher","first-page":"1872","DOI":"10.1016\/j.laa.2011.12.003","volume":"436","author":"Z Chebbi","year":"2012","unstructured":"Chebbi, Z., Moakher, M.: Means of hermitian positive-definite matrices based on the log-determinant alpha-divergence function. Linear Algebra Appl. 436(7), 1872\u20131889 (2012)","journal-title":"Linear Algebra Appl."},{"key":"51_CR30","first-page":"849","volume":"2","author":"AY Ng","year":"2002","unstructured":"Ng, A.Y., Jordan, M.I., Weiss, Y.: On spectral clustering: analysis and an algorithm. Adv. Neural Inf. Process. Syst. 2, 849\u2013856 (2002)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"51_CR31","doi-asserted-by":"crossref","unstructured":"Zhou, B., Tang, X., Wang, X.: Measuring crowd collectiveness. In: CVPR (2013)","DOI":"10.1109\/CVPR.2013.392"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2016 Workshops"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-48881-3_51","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T21:16:24Z","timestamp":1602278184000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-48881-3_51"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319488806","9783319488813"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-48881-3_51","relation":{"is-part-of":[{"id-type":"doi","id":"https:\/\/doi.org\/10.1007\/978-3-319-48881-3","asserted-by":"object"}]},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016]]},"assertion":[{"value":"3 November 2016","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2016","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2016","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 October 2016","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2016","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.eccv2016.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}