{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,3]],"date-time":"2024-07-03T01:32:34Z","timestamp":1719970354285},"reference-count":83,"publisher":"Springer Science and Business Media LLC","issue":"22","license":[{"start":{"date-parts":[[2016,11,23]],"date-time":"2016-11-23T00:00:00Z","timestamp":1479859200000},"content-version":"unspecified","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":[[2017,11]]},"DOI":"10.1007\/s11042-016-4156-x","type":"journal-article","created":{"date-parts":[[2016,11,23]],"date-time":"2016-11-23T02:06:18Z","timestamp":1479866778000},"page":"23777-23804","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A robust multimedia surveillance system for people counting"],"prefix":"10.1007","volume":"76","author":[{"given":"Zeyad Q. H.","family":"Al-Zaydi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David L.","family":"Ndzi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Munirah L.","family":"Kamarudin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ammar","family":"Zakaria","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ali Y. M.","family":"Shakaff","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,11,23]]},"reference":[{"key":"4156_CR1","volume-title":"Single pixel robust approach for background subtraction for fast people-counting and direction estimation","author":"AO Adegboye","year":"2013","unstructured":"Adegboye AO (2013) Single pixel robust approach for background subtraction for fast people-counting and direction estimation. University of Pretoria, Dissertation"},{"key":"4156_CR2","volume-title":"Single-pixel approach for fast people counting and direction estimation","author":"A Adegboye","year":"2012","unstructured":"Adegboye A, Hancke G, Jr GH (2012) Single-pixel approach for fast people counting and direction estimation. South. Africa Telecommun, Networks Appl"},{"key":"4156_CR3","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1016\/j.jvcir.2016.05.018","volume":"39","author":"ZQH Al-Zaydi","year":"2016","unstructured":"Al-Zaydi ZQH, Ndzi DL, Yang Y, Kamarudin ML (2016) An adaptive people counting system with dynamic features selection and occlusion handling. J Vis Commun Image Represent 39:218\u2013225. doi:\n10.1016\/j.jvcir.2016.05.018","journal-title":"J Vis Commun Image Represent"},{"key":"4156_CR4","volume-title":"Trajectories clustering in ICA space an application to automatic counting of pedestrians in video sequences","author":"G Antonini","year":"2004","unstructured":"Antonini G, Thiran JP (2004) Trajectories clustering in ICA space an application to automatic counting of pedestrians in video sequences. Adv. Concepts Intell. Vis, Syst"},{"key":"4156_CR5","doi-asserted-by":"publisher","first-page":"33003","DOI":"10.1117\/1.3456695","volume":"19","author":"Y Benezeth","year":"2010","unstructured":"Benezeth Y, Jodoin P-M, Emile B et al (2010) Comparative study of background subtraction algorithms. J Electron Imaging 19:33003. doi:\n10.1117\/1.3456695","journal-title":"J Electron Imaging"},{"key":"4156_CR6","volume-title":"Using dynamic time warping to find patterns in time series","author":"D Berndt","year":"1994","unstructured":"Berndt D, Clifford J (1994) Using dynamic time warping to find patterns in time series. Report, AAAI"},{"key":"4156_CR7","first-page":"2578","volume-title":"Speeding up k -means by approximating Euclidean distances via block vectors","author":"T Bottesch","year":"2016","unstructured":"Bottesch T, Markus K, Kaechele M, Ulm U (2016) Speeding up k -means by approximating Euclidean distances via block vectors. Int. Conf. Mach. Learn, In, pp. 2578\u20132586"},{"key":"4156_CR8","doi-asserted-by":"publisher","first-page":"219","DOI":"10.2174\/2213275910801030219","volume":"1","author":"T Bouwmans","year":"2008","unstructured":"Bouwmans T, El Baf F, Vachon B (2008) Background modeling using mixture of Gaussians for foreground detection - a survey. Recent Patents Comput Sci 1:219\u2013237. doi:\n10.2174\/2213275910801030219","journal-title":"Recent Patents Comput Sci"},{"key":"4156_CR9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.320","author":"GJ Brostow","year":"2006","unstructured":"Brostow GJ, Cipolla R (2006) Unsupervised Bayesian detection of independent motion in crowds. IEEE Conf Comput Vis Pattern Recognit. doi:\n10.1109\/CVPR.2006.320","journal-title":"IEEE Conf Comput Vis Pattern Recognit."},{"key":"4156_CR10","first-page":"2401","volume-title":"Towards a robust solution to people counting","author":"H \u00c7elik","year":"2006","unstructured":"\u00c7elik H, Hanjali\u0107 A, Hendriks EA (2006) Towards a robust solution to people counting. Int. Conf. Image Process, In, pp. 2401\u20132404"},{"key":"4156_CR11","first-page":"545","volume-title":"IEEE Int","author":"AB Chan","year":"2009","unstructured":"Chan AB, Vasconcelos N (2009) Bayesian poisson regression for crowd counting. In: IEEE Int. Conf, Comput. Vis. IEEE, pp. 545\u2013551"},{"key":"4156_CR12","doi-asserted-by":"publisher","first-page":"2160","DOI":"10.1109\/TIP.2011.2172800","volume":"21","author":"AB Chan","year":"2012","unstructured":"Chan AB, Vasconcelos N (2012) Counting people with low-level features and bayesian regression. IEEE Trans Image Process 21:2160\u20132177. doi:\n10.1109\/TIP.2011.2172800","journal-title":"IEEE Trans Image Process"},{"key":"4156_CR13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2008.4587569","author":"AB Chan","year":"2008","unstructured":"Chan AB, Liang ZSJ, Vasconcelos N (2008) Privacy preserving crowd monitoring: counting people without people models or tracking. IEEE Conf Comput Vis Pattern Recognit. doi:\n10.1109\/CVPR.2008.4587569","journal-title":"IEEE Conf Comput Vis Pattern Recognit"},{"key":"4156_CR14","first-page":"101","volume-title":"Perform","author":"A Chan","year":"2009","unstructured":"Chan A, Morrow M, Vasconcelos N (2009) Analysis of crowded scenes using holistic properties. In: Perform. Eval, Track. Surveill. Work. IEEE, pp. 101\u2013108"},{"key":"4156_CR15","first-page":"4672","volume-title":"Learning to count with back-propagated information","author":"K Chen","year":"2014","unstructured":"Chen K, Kamarainen J-K (2014) Learning to count with back-propagated information. Int. Conf. Pattern Recognit. IEEE, In, pp. 4672\u20134677"},{"key":"4156_CR16","doi-asserted-by":"publisher","DOI":"10.5244\/C.26.21","author":"K Chen","year":"2012","unstructured":"Chen K, Loy CC, Gong S, Xiang T (2012) Feature Mining for Localised Crowd Counting. Br Mach Vis Conf. doi:\n10.5244\/C.26.21","journal-title":"Br Mach Vis Conf"},{"key":"4156_CR17","first-page":"2467","volume-title":"IEEE Conf","author":"K Chen","year":"2013","unstructured":"Chen K, Gong S, Xiang T, Loy CC (2013) Cumulative attribute space for age and crowd density estimation. In: IEEE Conf. Comput, Vis. Pattern Recognit, pp. 2467\u20132474"},{"key":"4156_CR18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2008.4562983","author":"AM Cheriyadat","year":"2008","unstructured":"Cheriyadat AM, Bhaduri BL, Radke RJ (2008) Detecting multiple moving objects in crowded environments with coherent motion regions. IEEE Conf Comput Vis Pattern Recognit Work. doi:\n10.1109\/CVPRW.2008.4562983","journal-title":"IEEE Conf Comput Vis Pattern Recognit Work"},{"issue":"2","key":"4156_CR19","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1023\/A:1018781301409","volume":"10","author":"SY Cho","year":"1999","unstructured":"Cho SY, Chow TW (1999) A fast neural learning vision system for crowd estimation at underground stations platform. Neural Process Lett 10(2):111\u2013120","journal-title":"Neural Process Lett"},{"key":"4156_CR20","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1109\/3477.775269","volume":"29","author":"S-Y Cho","year":"1999","unstructured":"Cho S-Y, Chow T, Leung C (1999) A neural-based crowd estimation by hybrid global learning algorithm. IEEE Trans Syst Man, Cybern Part B Cybern 29:535\u2013541. doi:\n10.1109\/3477.775269","journal-title":"IEEE Trans Syst Man, Cybern Part B Cybern"},{"key":"4156_CR21","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1016\/S0954-1810(99)00016-3","volume":"13","author":"TWS Chow","year":"1999","unstructured":"Chow TWS, Yam JYF, Cho SY (1999) Fast training algorithm for feedforward neural networks: application to crowd estimation at underground stations. Artif Intell Eng 13:301\u2013307. doi:\n10.1016\/S0954-1810(99)00016-3","journal-title":"Artif Intell Eng"},{"key":"4156_CR22","volume-title":"(2010) counting moving people in videos by salient points detection","author":"D Conte","year":"1743","unstructured":"Conte D, Foggia P, Percannella G et al (1743\u20131746) (2010) counting moving people in videos by salient points detection. Int. Conf. Pattern Recognit. pp, In"},{"key":"4156_CR23","first-page":"225","volume-title":"IEEE Int","author":"D Conte","year":"2010","unstructured":"Conte D, Foggia P, Percannella G et al (2010) A method for counting people in crowded scenes. In: IEEE Int. Conf, Adv. Video Signal Based Surveill, pp. 225\u2013232"},{"key":"4156_CR24","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1007\/s00138-013-0491-3","volume":"24","author":"D Conte","year":"2013","unstructured":"Conte D, Foggia P, Percannella G, Vento M (2013) Counting moving persons in crowded scenes. Mach Vis Appl 24:1029\u20131042. doi:\n10.1007\/s00138-013-0491-3","journal-title":"Mach Vis Appl"},{"key":"4156_CR25","first-page":"886","volume-title":"IEEE Conf","author":"N Dalal","year":"2005","unstructured":"Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE Conf. Comput, Vis. Pattern Recognit, pp. 886\u2013893"},{"key":"4156_CR26","doi-asserted-by":"publisher","DOI":"10.1049\/ecej:19950106","author":"A Davies","year":"1995","unstructured":"Davies A, Yin JH, Velastin S (1995) Crowd monitoring using image processing. Electron Commun Eng J. doi:\n10.1049\/ecej:19950106","journal-title":"Electron Commun Eng J"},{"key":"4156_CR27","doi-asserted-by":"publisher","DOI":"10.5244\/C.24.68","author":"P Dollar","year":"2010","unstructured":"Dollar P, Belongie S, Perona P (2010) The fastest pedestrian detector in the west. Br Mach Vis Conf. doi:\n10.5244\/C.24.68","journal-title":"Br Mach Vis Conf."},{"key":"4156_CR28","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1109\/TPAMI.2009.167","volume":"32","author":"PF Felzenszwalb","year":"2010","unstructured":"Felzenszwalb PF, Girshick RB, McAllester D, Ramanan D (2010) Object detection with discriminative trained part based models. IEEE Trans Pattern Anal Mach Intell 32:1627\u20131645","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"4156_CR29","first-page":"246","volume-title":"Low level crowd analysis using frame-wise normalized feature for people counting","author":"H Fradi","year":"2012","unstructured":"Fradi H, Dugelay JL (2012) Low level crowd analysis using frame-wise normalized feature for people counting. Int. Work. Inf. Forensics Secur, In, pp. 246\u2013251"},{"key":"4156_CR30","unstructured":"Gao L, Wang Y, Ye X, Wang J (2016) Crowd Pedestrian Counting Considering Network Flow Constraints in Videos. arXiv Prepr"},{"key":"4156_CR31","first-page":"2913","volume-title":"Comput","author":"W Ge","year":"2009","unstructured":"Ge W, Collins RT (2009) Marked point processes for crowd counting. In: Comput. Vis, Pattern Recognit. Work. IEEE, pp. 2913\u20132920"},{"key":"4156_CR32","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-3869-1","author":"A Hafeezallah","year":"2016","unstructured":"Hafeezallah A, Abu-Bakar S (2016) Crowd counting using statistical features based on curvelet frame change detection. Multimed Tools Appl. doi:\n10.1007\/s11042-016-3869-1","journal-title":"Multimed Tools Appl"},{"key":"4156_CR33","first-page":"67","volume-title":"Stereo person tracking with adaptive plan-view statistical templates","author":"M Harville","year":"2002","unstructured":"Harville M (2002) Stereo person tracking with adaptive plan-view statistical templates. Proc. ECCV Work. Stat. Methods Video Process, In, pp. 67\u201372"},{"key":"4156_CR34","first-page":"1291","volume-title":"People count system using multi-sensing application","author":"K Hashimoto","year":"1997","unstructured":"Hashimoto K, Morinaka K, Yoshiike N et al (1997) People count system using multi-sensing application. Int. Solid State Sensors Actuators Conf, In, pp. 1291\u20131294"},{"key":"4156_CR35","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1109\/TSMCA.2010.2064299","volume":"41","author":"YL Hou","year":"2011","unstructured":"Hou YL, Pang GKH (2011) People counting and human detection in a challenging situation. IEEE Trans Syst Man, Cybern Part ASystems Humans 41:24\u201333. doi:\n10.1109\/TSMCA.2010.2064299","journal-title":"IEEE Trans Syst Man, Cybern Part ASystems Humans"},{"key":"4156_CR36","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.ijleo.2014.08.132","volume":"126","author":"X Hu","year":"2015","unstructured":"Hu X, Zheng H, Chen Y, Chen L (2015) Dense crowd counting based on perspective weight model using a fisheye camera. Int J Light Electron Opt 126:123\u2013130. doi:\n10.1016\/j.ijleo.2014.08.132","journal-title":"Int J Light Electron Opt"},{"key":"4156_CR37","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1016\/j.jvcir.2016.03.021","volume":"38","author":"Y Hu","year":"2016","unstructured":"Hu Y, Chang H, Nian F et al (2016) Dense crowd counting from still images with convolutional neural networks. J Vis Commun Image Represent 38:530\u2013539. doi:\n10.1016\/j.jvcir.2016.03.021","journal-title":"J Vis Commun Image Represent"},{"key":"4156_CR38","volume-title":"Cost-sensitive sparse linear regression for crowd counting with imbalanced training data","author":"X Huang","year":"2016","unstructured":"Huang X, Zou Y, Wang Y (2016) Cost-sensitive sparse linear regression for crowd counting with imbalanced training data. IEEE Int. Conf. Multimed, Expo"},{"key":"4156_CR39","unstructured":"Intelcom DILAX (2015) Public Transport \nhttps:\/\/www.dilax.com\/\n\n. Accessed 1 Oct 2016"},{"key":"4156_CR40","first-page":"4545","volume-title":"IEEE Int","author":"CY Jeong","year":"2013","unstructured":"Jeong CY, Choi S, Han SW (2013) A method for counting moving and stationary people by interest point classification. In: IEEE Int. Conf, Image Process. IEEE, pp. 4545\u20134548"},{"key":"4156_CR41","first-page":"17","volume":"96","author":"NS Joshi","year":"2014","unstructured":"Joshi NS, Choubey NS (2014) Comparison of traditional approach for edge detection with soft computing approach. Int J Comput Appl 96:17\u201323","journal-title":"Int J Comput Appl"},{"key":"4156_CR42","first-page":"24","volume":"102","author":"G Kaur","year":"2014","unstructured":"Kaur G, Virk IS (2014) Edge detection through fuzzy system using type I format. Int J Comput Appl 102:24\u201327","journal-title":"Int J Comput Appl"},{"key":"4156_CR43","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.cviu.2007.02.003","volume":"110","author":"P Kilambi","year":"2008","unstructured":"Kilambi P, Ribnick E, Joshi AJ et al (2008) Estimating pedestrian counts in groups. Comput Vis Image Underst 110:43\u201359. doi:\n10.1016\/j.cviu.2007.02.003","journal-title":"Comput Vis Image Underst"},{"key":"4156_CR44","doi-asserted-by":"publisher","DOI":"10.5244\/C.19.63","author":"D Kong","year":"2005","unstructured":"Kong D, Gray D, Tao H (2005) Counting pedestrians in crowds using viewpoint invariant training. Procedings Br Mach Vis Conf. doi:\n10.5244\/C.19.63","journal-title":"Procedings Br Mach Vis Conf"},{"key":"4156_CR45","first-page":"1187","volume-title":"A viewpoint invariant approach for crowd counting","author":"D Kong","year":"2006","unstructured":"Kong D, Gray D, Tao H (2006) A viewpoint invariant approach for crowd counting. Int. Conf. Pattern Recognit, In, pp. 1187\u20131190"},{"key":"4156_CR46","first-page":"878","volume-title":"IEEE Conf","author":"B Leibe","year":"2005","unstructured":"Leibe B, Seemann E, Schiele B (2005) Pedestrian detection in crowded scenes. In: IEEE Conf. Comput, Vis. Pattern Recognit, pp. 878\u2013885"},{"key":"4156_CR47","first-page":"1324","volume-title":"Learning to count objects in images","author":"V Lempitsky","year":"2010","unstructured":"Lempitsky V, Zisserman A (2010) Learning to count objects in images. Adv. Neural Inf. Process. Syst, In, pp. 1324\u20131332"},{"key":"4156_CR48","first-page":"54","volume-title":"Robust people counting in video surveillance: dataset and system","author":"J Li","year":"2011","unstructured":"Li J, Huang L, Liu C (2011) Robust people counting in video surveillance: dataset and system. Int. Conf. Adv. Video Signal Based Surveill, In, pp. 54\u201359"},{"key":"4156_CR49","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1109\/3468.983420","volume":"31","author":"S Lin","year":"2001","unstructured":"Lin S, Chen J, Chao H (2001) Estimation of number of people in crowded scenes using perspective transformation. IEEE Trans Syst Man Cybern 31:645\u2013654","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"4156_CR50","first-page":"347","volume-title":"Crowd counting and profiling: methodology and evaluation","author":"C Loy","year":"2013","unstructured":"Loy C, Chen K, Gong S, Xiang T (2013) Crowd counting and profiling: methodology and evaluation. Model. Simul. Vis. Anal. Crowds. Springer New York, In, pp. 347\u2013382"},{"key":"4156_CR51","unstructured":"Ltd B (2013) Use CCTV to Count People \nhttp:\/\/www.videoturnstile.com\/\n\n. Accessed 1 Oct 2016"},{"key":"4156_CR52","first-page":"1","volume-title":"IEEE Conf","author":"R Ma","year":"2004","unstructured":"Ma R, Li L, Huang W, Tian Q (2004) On pixel count based crowd density estimation for visual surveillance. In: IEEE Conf. Cybern, Intell. Syst. IEEE, pp. 1\u20133"},{"key":"4156_CR53","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2089094.2089107","volume":"3","author":"H Ma","year":"2012","unstructured":"Ma H, Zeng C, Ling CX (2012) A reliable people counting system via multiple cameras. ACM Trans Intell Syst Technol 3:1\u201322. doi:\n10.1145\/2089094.2089107","journal-title":"ACM Trans Intell Syst Technol"},{"key":"4156_CR54","first-page":"233","volume-title":"Fast people counting using head detection from skeleton graph","author":"D Merad","year":"2010","unstructured":"Merad D, Aziz KE, Thome N (2010) Fast people counting using head detection from skeleton graph. Adv. Video Signal Based Surveill. IEEE, In, pp. 233\u2013240"},{"key":"4156_CR55","first-page":"110","volume":"2","author":"C Norris","year":"2004","unstructured":"Norris C, Mccahill M, Wood D (2004) Editorial. The growth of CCTV: a global perspective on the international diffusion of video surveillance in publicly accessible space. Surveill Soc 2:110\u2013135","journal-title":"Surveill Soc"},{"key":"4156_CR56","first-page":"705","volume-title":"IEEE Conf","author":"V Rabaud","year":"2006","unstructured":"Rabaud V, Belongie S (2006) Counting crowded moving objects. In: IEEE Conf. Comput, Vis. Pattern Recognit, pp. 705\u2013711"},{"key":"4156_CR57","doi-asserted-by":"publisher","first-page":"1533","DOI":"10.1007\/s00371-014-1032-4","volume":"31","author":"AS Rao","year":"2015","unstructured":"Rao AS, Gubbi J, Marusic S, Palaniswami M (2015) Estimation of crowd density by clustering motion cues. Vis Comput 31:1533\u20131552. doi:\n10.1007\/s00371-014-1032-4","journal-title":"Vis Comput"},{"key":"4156_CR58","first-page":"2423","volume-title":"Density-aware person detection and tracking in crowds","author":"M Rodriguez","year":"2011","unstructured":"Rodriguez M, Superieure EN, Laptev I et al (2011) Density-aware person detection and tracking in crowds. Int. Conf. Comput. Vis. IEEE, In, pp. 2423\u20132430"},{"key":"4156_CR59","volume-title":"Crowd monitoring using computer vision","author":"DA Ryan","year":"2013","unstructured":"Ryan DA (2013) Crowd monitoring using computer vision. Queensland University of Technology, Dissertation"},{"key":"4156_CR60","first-page":"81","volume-title":"Crowd counting using multiple local features","author":"D Ryan","year":"2009","unstructured":"Ryan D, Denman S, Fookes C, Sridharan S (2009) Crowd counting using multiple local features. Digit. Image Comput. Tech. Appl. IEEE, In, pp. 81\u201388"},{"key":"4156_CR61","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.patrec.2013.10.002","volume":"44","author":"D Ryan","year":"2014","unstructured":"Ryan D, Denman S, Fookes C, Sridharan S (2014) Scene invariant multi camera crowd counting. Pattern Recogn Lett 44:98\u2013112. doi:\n10.1016\/j.patrec.2013.10.002","journal-title":"Pattern Recogn Lett"},{"key":"4156_CR62","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cviu.2014.07.008","volume":"130","author":"D Ryan","year":"2015","unstructured":"Ryan D, Denman S, Sridharan S, Fookes C (2015) An evaluation of crowd counting methods, features and regression models. Comput Vis Image Underst 130:1\u201317. doi:\n10.1016\/j.cviu.2014.07.008","journal-title":"Comput Vis Image Underst"},{"key":"4156_CR63","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.engappai.2015.01.007","volume":"41","author":"SAM Saleh","year":"2015","unstructured":"Saleh SAM, Suandi SA, Ibrahim H (2015) Recent survey on crowd density estimation and counting for visual surveillance. Eng Appl Artif Intell 41:103\u2013114. doi:\n10.1016\/j.engappai.2015.01.007","journal-title":"Eng Appl Artif Intell"},{"key":"4156_CR64","first-page":"53","volume":"3","author":"R Shbib","year":"2013","unstructured":"Shbib R, Zhou S, Ndzi D, Al-kadhimi K (2013) Distributed monitoring system based on weighted data fusing model. Am J Soc Issues Humanit 3:53\u201362","journal-title":"Am J Soc Issues Humanit"},{"key":"4156_CR65","unstructured":"ShopperTrak (2013) ShopperTrak Solutions \nhttp:\/\/www.shoppertrak.com\/\n\n. Accessed 1 Oct 2016"},{"key":"4156_CR66","unstructured":"Shrivakshan GT, Chandrasekar C (2012) A Comparison of various Edge Detection Techniques used in Image Processing Int J Comput Sci Issues:9"},{"key":"4156_CR67","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2006.91","author":"O Sidla","year":"2006","unstructured":"Sidla O, Lypetskyy Y, Br\u00e4ndle N, Seer S (2006) Pedestrian detection and tracking for counting applications in crowded situations. IEEE Int Conf Video Signal Based Surveill. doi:\n10.1109\/AVSS.2006.91","journal-title":"IEEE Int Conf Video Signal Based Surveill"},{"key":"4156_CR68","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.cviu.2013.12.005","volume":"122","author":"A Sobral","year":"2014","unstructured":"Sobral A, Vacavant A (2014) A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos. Comput Vis Image Underst 122:4\u201321. doi:\n10.1016\/j.cviu.2013.12.005","journal-title":"Comput Vis Image Underst"},{"key":"4156_CR69","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1109\/TIP.2014.2363445","volume":"24","author":"NC Tang","year":"2015","unstructured":"Tang NC, Lin Y-Y, Weng M, Liao HM (2015) Cross-camera knowledge transfer for Multiview people counting. IEEE Trans Image Process 24:80\u201393. doi:\n10.1109\/TIP.2014.2363445","journal-title":"IEEE Trans Image Process"},{"key":"4156_CR70","unstructured":"Technology A (2013) Our customers \nhttp:\/\/www.peoplecounting.co.uk\/our-customers\n\n. Accessed 1 Oct 2016"},{"key":"4156_CR71","first-page":"313","volume-title":"IEEE Int","author":"IS Topkaya","year":"2014","unstructured":"Topkaya IS, Erdogan H, Porikli F (2014) Counting people by clustering person detector outputs. In: IEEE Int. Conf, Adv. Video Signal Based Surveill. IEEE, pp. 313\u2013318"},{"key":"4156_CR72","first-page":"3340","volume-title":"IEEE Int","author":"J Tu","year":"2013","unstructured":"Tu J, Zhang C, Hao P (2013) Robust real-time attention-based head-shoulder detection for video surveillance. In: IEEE Int. Conf, Image Process. IEEE, pp. 3340\u20133344"},{"key":"4156_CR73","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.75","author":"O Tuzel","year":"2008","unstructured":"Tuzel O, Porikli F, Meer P (2008) Pedestrian detection via classification on Riemannian manifolds. IEEE Trans Pattern Anal Mach Intell. doi:\n10.1109\/TPAMI.2008.75","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"4156_CR74","volume-title":"Data assimilation for agent-based simulation of smart environment","author":"M Wang","year":"2014","unstructured":"Wang M (2014) Data assimilation for agent-based simulation of smart environment. Georgia State University, Dissertation"},{"key":"4156_CR75","first-page":"3401","volume-title":"IEEE Conf","author":"M Wang","year":"2011","unstructured":"Wang M, Wang X (2011) Automatic adaptation of a generic pedestrian detector to a specific traffic scene. In: IEEE Conf. Comput, Vis. Pattern Recognit, pp. 3401\u20133408"},{"key":"4156_CR76","doi-asserted-by":"crossref","first-page":"1620","DOI":"10.1109\/TCSVT.2014.2308616","volume":"24","author":"J Wang","year":"2014","unstructured":"Wang J, Fu W, Liu J et al (2014) Spatiotemporal group context for pedestrian counting. IEEE Trans Circuits Syst Video Technol 24:1620\u20131630","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"4156_CR77","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s11263-006-0027-7","volume":"75","author":"B Wu","year":"2007","unstructured":"Wu B, Nevatia R (2007) Detection and tracking of multiple, partially occluded humans by Bayesian combination of edgelet based part detectors. Int J Comput Vis 75:247\u2013266. doi:\n10.1007\/s11263-006-0027-7","journal-title":"Int J Comput Vis"},{"key":"4156_CR78","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1191\/0142331206tim178oa","volume":"28","author":"L Xiaohua","year":"2006","unstructured":"Xiaohua L, Lansun S, Huanqin L (2006) Estimation of crowd density based on wavelet and support vector machine. Trans Inst Meas Control 28:299\u2013308. doi:\n10.1191\/0142331206tim178oa","journal-title":"Trans Inst Meas Control"},{"key":"4156_CR79","doi-asserted-by":"crossref","first-page":"2349","DOI":"10.1109\/LSP.2015.2481930","volume":"22","author":"X Xing","year":"2015","unstructured":"Xing X, Wang K, Lv Z (2015) Fusion of gait and facial features using coupled projections for people identification at a distance. Signal Process Lett 22:2349\u20132353","journal-title":"Signal Process Lett"},{"key":"4156_CR80","first-page":"1","volume-title":"Crowd density estimation based on rich features and random projection Forest","author":"B Xu","year":"2016","unstructured":"Xu B, Qiu G (2016) Crowd density estimation based on rich features and random projection Forest. IEEE Winter Appl. Comput. Vis, In, pp. 1\u20138"},{"key":"4156_CR81","doi-asserted-by":"publisher","first-page":"1037","DOI":"10.1109\/TITS.2011.2132759","volume":"12","author":"J Zhang","year":"2011","unstructured":"Zhang J, Tan B, Sha F, He L (2011) Predicting pedestrian counts in crowded scenes with rich and high-dimensional features. IEEE Trans Intell Transp Syst 12:1037\u20131046. doi:\n10.1109\/TITS.2011.2132759","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"4156_CR82","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298684","author":"C Zhang","year":"2015","unstructured":"Zhang C, Li H, Wang X (2015a) Cross-scene crowd counting via deep convolutional neural networks. Proc IEEE Conf Comput Vis Pattern Recognit. doi:\n10.1109\/CVPR.2015.7298684","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"4156_CR83","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.neucom.2015.03.083","volume":"166","author":"Z Zhang","year":"2015","unstructured":"Zhang Z, Wang M, Geng X (2015b) Crowd counting in public video surveillance by label distribution learning. Neurocomputing 166:151\u2013163. doi:\n10.1016\/j.neucom.2015.03.083","journal-title":"Neurocomputing"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-016-4156-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-016-4156-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-016-4156-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,10,27]],"date-time":"2017-10-27T00:35:21Z","timestamp":1509064521000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-016-4156-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11,23]]},"references-count":83,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2017,11]]}},"alternative-id":["4156"],"URL":"https:\/\/doi.org\/10.1007\/s11042-016-4156-x","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,11,23]]}}}