{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T21:48:28Z","timestamp":1765057708070},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T00:00:00Z","timestamp":1604016000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T00:00:00Z","timestamp":1604016000000},"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":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1007\/s11042-020-09897-0","type":"journal-article","created":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T13:02:41Z","timestamp":1604062961000},"page":"7637-7651","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A novel background updation algorithm using fuzzy c-means clustering for pedestrian detection"],"prefix":"10.1007","volume":"80","author":[{"given":"Harshitha","family":"Malireddi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kiran","family":"Parwani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B","family":"Rajitha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,30]]},"reference":[{"key":"9897_CR1","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1007\/s00138-010-0262-3","volume":"22","author":"VM Antoni","year":"2011","unstructured":"Antoni VM, Chan B, Vasconcelos N (2011) Generalized stauffer\u2013grimson background subtraction for dynamic scenes. Mach Vis Applicat 22:751\u2013766","journal-title":"Mach Vis Applicat"},{"key":"9897_CR2","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.jvcir.2016.12.015","volume":"43","author":"SR Arashloo","year":"2017","unstructured":"Arashloo SR, Amirani MC, Noroozi A (2017) Dynamic texture representation using a deep multi-scale convolutional network. J Vis Commun Image Represent 43:89\u201397","journal-title":"J Vis Commun Image Represent"},{"issue":"3","key":"9897_CR3","doi-asserted-by":"publisher","first-page":"219","DOI":"10.2174\/2213275910801030219","volume":"1","author":"T Bouwmans","year":"2008","unstructured":"Bouwmans T, Baf FE, Vachon B (2008) Background modeling using mixture of gaussians for foreground detection - a survey. Recent Patents Comput Sci 1(3):219\u2013237","journal-title":"Recent Patents Comput Sci"},{"key":"9897_CR4","first-page":"4","volume":"3","author":"T Bouwmans","year":"2011","unstructured":"Bouwmans T (2011) Recent advanced statistical background modeling for foreground detection: a systematic survey. Recent Patents Comput Sci 3:4","journal-title":"Recent Patents Comput Sci"},{"key":"9897_CR5","unstructured":"Baf FE, Bouwmans T, Vachon B (2008) A fuzzy approach for background subtraction. In: Proceedings of ICIP. IEEE, pp 2648\u20132651"},{"key":"9897_CR6","unstructured":"Beiping H, Wen Z (2010) Moving target classification based on shape features from real-time video. Chinese Journal of Scientific Instrument, vol 31, pp 1819\u20131825"},{"key":"9897_CR7","doi-asserted-by":"crossref","unstructured":"Cheng EJ, Prasad M, Yang J, Khanna P, Chen B-H, Tao X, Young K-Y, Lin C-T A fast fused part-based model with new deep feature for pedestrian detection and security monitoring. Measurement (2019):107081","DOI":"10.1016\/j.measurement.2019.107081"},{"issue":"6","key":"9897_CR8","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1109\/TCYB.2013.2274330","volume":"44","author":"P Chiranjeevi","year":"2014","unstructured":"Chiranjeevi P, Sengupta S (2014) Detection of moving objects using multi-channel kernel fuzzy correlogram based background subtraction. IEEE Trans Cybern 44(6):870\u2013881","journal-title":"IEEE Trans Cybern"},{"key":"9897_CR9","doi-asserted-by":"crossref","unstructured":"Dalal N, Triggs B (2005) Histograms of Oriented Gradients for Human Detection. IEEE Conference on Computer Vision and Pattern Recognition, vol 1, , San Diego, pp 886\u2013893","DOI":"10.1109\/CVPR.2005.177"},{"key":"9897_CR10","doi-asserted-by":"crossref","unstructured":"Davis J, Goadrich M (2006) The relationship between precision-recall and roc curves. In: Proc. of 23rd Int. Conf. Machine Learning. ACM Press, pp 233\u2013240","DOI":"10.1145\/1143844.1143874"},{"issue":"4","key":"9897_CR11","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1109\/TPAMI.2011.155","volume":"34","author":"P Dollar","year":"2011","unstructured":"Dollar P, Wojek C, Schiele B, Perona P (2011) Pedestrian detection: an evaluation of the state of the art. IEEE Trans Pattern Anal Mach Intellx 34(4):743\u2013761","journal-title":"IEEE Trans Pattern Anal Mach Intellx"},{"key":"9897_CR12","doi-asserted-by":"crossref","unstructured":"Elgammal A, Harwood D, Davis L (2000) Non-parametric model for background subtraction Computer vision\u2013ECCV 2000Springer, pp 751\u2013767","DOI":"10.1007\/3-540-45053-X_48"},{"key":"9897_CR13","doi-asserted-by":"crossref","unstructured":"Gao D, Han S (2009) Discriminate saliency, the detection of suspicious coincidences, and application to visual recognition. IEEE Transaction On PAMI, vol 31, pp 989\u20131003","DOI":"10.1109\/TPAMI.2009.27"},{"key":"9897_CR14","doi-asserted-by":"crossref","unstructured":"Gavrila D (2000) Pedestrian detection from a moving vehicle. European Conference on Computer Vision, Ireland, pp 37\u201349","DOI":"10.1007\/3-540-45053-X_3"},{"issue":"2","key":"9897_CR15","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/s10462-017-9542-x","volume":"50","author":"K Goyal","year":"2018","unstructured":"Goyal K, Singhai J (2018) Review of background subtraction methods using Gaussian mixture model for video surveillance systems. Artif Intell Rev 50(2):241\u2013259","journal-title":"Artif Intell Rev"},{"issue":"8","key":"9897_CR16","doi-asserted-by":"publisher","first-page":"759","DOI":"10.1109\/LSP.2013.2263800","volume":"20","author":"KK Hati","year":"2013","unstructured":"Hati KK, Sa PK, Majhi B (2013) Intensity range based background subtraction for effective object detection. IEEE Signal Process Lett 20(8):759\u2013762","journal-title":"IEEE Signal Process Lett"},{"issue":"4","key":"9897_CR17","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1109\/TPAMI.2006.68","volume":"28","author":"M Heikkil\u00e4","year":"2006","unstructured":"Heikkil\u00e4 M, Pietik\u00e4inen M (2006) A texture-based method for modeling the background and detecting moving objects. IEEE Trans Patt Anal Mach Intell 28(4):657\u2013662","journal-title":"IEEE Trans Patt Anal Mach Intell"},{"key":"9897_CR18","unstructured":"I2R dataset link, http:\/\/vis-www.cs.umass.edu\/~narayana\/castanza\/I2Rdataset\/"},{"key":"9897_CR19","doi-asserted-by":"crossref","unstructured":"Jiang Y, Tong G, Yin H, Xiong N (2019) A Pedestrian Detection Method Based on Genetic Algorithm for Optimize XGBoost Training Parameters. IEEE Access 7:118310\u2013118321","DOI":"10.1109\/ACCESS.2019.2936454"},{"key":"9897_CR20","unstructured":"Lampert CH, Blaschko MB, Hofmann T (2008) Beyond sliding windows: Object localization by efficient sub window search. IEEE Conference on Computer Vision and Pattern Recognition, Anchorage , pp 1\u20138"},{"key":"9897_CR21","first-page":"1150","volume":"2","author":"D Lowe","year":"1999","unstructured":"Lowe D (1999) Object recognition from local scale-invariant features. Proc Int Conf Comput Vis 2:1150\u20131157","journal-title":"Proc Int Conf Comput Vis"},{"key":"9897_CR22","doi-asserted-by":"crossref","unstructured":"Mikolajczyk K, Schmid C, Zisserman A (2004) Human detection based on a probabilistic assembly of robust part detectors. Proceeding of the European Conference on Computer Vision, 69\u201382","DOI":"10.1007\/978-3-540-24670-1_6"},{"key":"9897_CR23","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.patrec.2017.03.010","volume":"96","author":"T Minematsu","year":"2017","unstructured":"Minematsu T, Uchiyama H, Shimada A, Nagahara H, Taniguchi R-I (2017) Adaptive background model registration for moving cameras. Pattern Recogn Lett 96:86\u201395","journal-title":"Pattern Recogn Lett"},{"key":"9897_CR24","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1109\/34.917571","volume":"23","author":"A Mohan","year":"2001","unstructured":"Mohan A, Papageorgiou C (2001) Example-based object detection in images by components. IEEE Trans PAMI 23:349\u2013361","journal-title":"IEEE Trans PAMI"},{"key":"9897_CR25","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1016\/j.imavis.2009.06.006","volume":"28","author":"S Montabone","year":"2010","unstructured":"Montabone S, soto A (2010) Human detection using a mobile platform and novel features derived from a visual saliency mechanism. Image Vis Comput 28:391\u2013402","journal-title":"Image Vis Comput"},{"key":"9897_CR26","doi-asserted-by":"crossref","unstructured":"Perko R, Leonardis A (2010) A framework for visual context- aware object detection in still images. Computer Vision and Image Understanding, vol 114, pp 700\u2013711","DOI":"10.1016\/j.cviu.2010.03.005"},{"key":"9897_CR27","unstructured":"PETS 2012 dataset link, http:\/\/www.cvg.reading.ac.uk\/PETS2012\/a.html"},{"issue":"4","key":"9897_CR28","doi-asserted-by":"publisher","first-page":"1684","DOI":"10.1016\/j.patcog.2011.10.001","volume":"45","author":"A Sanin","year":"2012","unstructured":"Sanin A, Sanderson C, Lovell BC (2012) Shadow Detection: a survey and comparative evaluation of recent methods. Pattern Recogn 45(4):1684\u20131695","journal-title":"Pattern Recogn"},{"key":"9897_CR29","doi-asserted-by":"crossref","unstructured":"Vapnik VN (1995) The nature of statistical learning theory. Springer, Berlin","DOI":"10.1007\/978-1-4757-2440-0"},{"key":"9897_CR30","unstructured":"Wallflower dataset link, https:\/\/www.microsoft.com\/en-us\/download\/details.aspx?id=854651"},{"key":"9897_CR31","unstructured":"Wallach PJ (2015) Mathematics in Contemporary Society Chapter 7. CUNY Academic Works"},{"key":"9897_CR32","doi-asserted-by":"crossref","unstructured":"Wang X (2009) An HOG-LBP human detector with partial occlusion handling. IEEE International Conference on Computer Vision","DOI":"10.1109\/ICCV.2009.5459207"},{"key":"9897_CR33","unstructured":"Xu L, Ren JSJ, Ce L, Jia J (2014) Deep convolutional neural network for image deconvolution advances in neural information processing systems 27 (NIPS)"},{"key":"9897_CR34","doi-asserted-by":"crossref","unstructured":"Xiaoping L, Songze L, Boxing Z, Yanhong W, Feng X (2019) Fast Aerial UAV Detection Using Improved Inter-frame Difference and SVM. J Phys Conf Ser 1187(3):032082. IOP Publishing","DOI":"10.1088\/1742-6596\/1187\/3\/032082"},{"key":"9897_CR35","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.cosrev.2018.03.001","volume":"28","author":"M Yazdi","year":"2018","unstructured":"Yazdi M, Bouwmans T (2018) New trends on moving object detection in video images captured by a moving camera A survey. Comput Sci Rev 28:157\u2013177","journal-title":"Comput Sci Rev"},{"key":"9897_CR36","unstructured":"Yi M, Kwang KY, Kim SW, Chang HJ, Choi JY (2013) Detection of moving objects with non-stationary cameras in 5.8 ms Bringing motion detection to your mobile device. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp 27\u201334"},{"key":"9897_CR37","unstructured":"Zhu Q, Avidan S (2006) Fast human detection using cascade of histograms of oriented gradients. IEEE Computer Society Conference on Computer Vision and Pattern Recognition"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09897-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-020-09897-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09897-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,24]],"date-time":"2021-02-24T23:52:32Z","timestamp":1614210752000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-020-09897-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,30]]},"references-count":37,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["9897"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09897-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,30]]},"assertion":[{"value":"3 May 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 September 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}