{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T15:06:34Z","timestamp":1724079994546},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"20","license":[{"start":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T00:00:00Z","timestamp":1648684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T00:00:00Z","timestamp":1648684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2022,8]]},"DOI":"10.1007\/s11042-022-12422-0","type":"journal-article","created":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T08:04:41Z","timestamp":1648713881000},"page":"28849-28874","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Corner based statistical modelling in vehicle detection under various condition for traffic surveillance"],"prefix":"10.1007","volume":"81","author":[{"given":"Mallikarjun","family":"Anandhalli","sequence":"first","affiliation":[]},{"given":"Tanuja","family":"A","sequence":"additional","affiliation":[]},{"given":"Vishwanath P.","family":"Baligar","sequence":"additional","affiliation":[]},{"given":"Pavana","family":"Baligar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,3,31]]},"reference":[{"issue":"3","key":"12422_CR1","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1515\/jisys-2016-0073","volume":"27","author":"M Anandhalli","year":"2018","unstructured":"Anandhalli M, Baligar VP (2018) An approach to detect vehicles in multiple climatic conditions using the corner point approach. J. Intell. Syst. 27 (3):363\u2013376","journal-title":"J. Intell. Syst."},{"key":"12422_CR2","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1109\/SAI.2017.8252170","volume":"2017","author":"RKC Billones","year":"2017","unstructured":"Billones RKC, Bandala AA, Sybingco E, Gan Lim LA, Fillone AD, Dadios EP (2017) Vehicle detection and tracking using corner feature points and artificial neural networks for a vision-based contactless apprehension system. Computing Conference 2017:688\u2013691. https:\/\/doi.org\/10.1109\/SAI.2017.8252170","journal-title":"Computing Conference"},{"key":"12422_CR3","doi-asserted-by":"publisher","unstructured":"Cai Y, Wang H, Zheng Z, Sun X (2017) Scene-Adaptive Vehicle Detection Algorithm Based on a Composite Deep Structure. In: IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2017.2756081, vol 5, pp 22804\u201322811","DOI":"10.1109\/ACCESS.2017.2756081"},{"key":"12422_CR4","unstructured":"Change Detection Benchmark Web Site [(accessed on 24 January 2020)]; Available online: http:\/\/jacarini.dinf.usherbrooke.ca\/dataset2014"},{"key":"12422_CR5","doi-asserted-by":"publisher","unstructured":"Chen Y, Wusheng H (2020) Robust vehicle detection and counting algorithm adapted to complex traffic environments with sudden illumination changes and shadows sensors (basel) 2020 may; 20(9): 2686, Published online. https:\/\/doi.org\/10.3390\/s20092686","DOI":"10.3390\/s20092686"},{"key":"12422_CR6","doi-asserted-by":"publisher","unstructured":"Dooley D, McGinley B, Hughes C, Kilmartin L, Jones E, Glavin M (Jan. 2016) A Blind-Zone Detection Method Using a Rear-Mounted Fisheye Camera With Combination of Vehicle Detection Methods. In: IEEE Transactions on Intelligent Transportation Systems. https:\/\/doi.org\/10.1109\/TITS.2015.2467357, vol 17, pp 264\u2013278","DOI":"10.1109\/TITS.2015.2467357"},{"key":"12422_CR7","doi-asserted-by":"publisher","unstructured":"Enjat Munajat MD, Widyantoro DH, Munir R (2016) Vehicle detection and tracking based on corner and lines adjacent detection features, 2016 2nd International Conference on Science in Information Technology (ICSITech), pp. 244-249, https:\/\/doi.org\/10.1109\/ICSITech.2016.7852641","DOI":"10.1109\/ICSITech.2016.7852641"},{"key":"12422_CR8","doi-asserted-by":"publisher","unstructured":"Feng R, Fan C, Li Z, Chen X (2020) Mixed Road User Trajectory Extraction From Moving Aerial Videos Based on Convolution Neural Network Detection. In: IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2020.2976890, vol 8, pp 43508\u201343519","DOI":"10.1109\/ACCESS.2020.2976890"},{"key":"12422_CR9","doi-asserted-by":"crossref","unstructured":"Geiger A, Lenz P, Urtasun R (2012) Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite geiger2012CVPR","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"12422_CR10","doi-asserted-by":"publisher","first-page":"14497","DOI":"10.1007\/s00521-019-04486-1","volume":"32","author":"LY Hao","year":"2020","unstructured":"Hao LY, Li J, Guo G (2020) A multi-target corner pooling-based neural network for vehicle detection. Neural Comput & Applic 32:14497\u201314506","journal-title":"Neural Comput & Applic"},{"key":"12422_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/IWAIT.2018.8369767","volume":"2018","author":"S Hsu","year":"2018","unstructured":"Hsu S, Huang C, Chuang C (2018) Vehicle detection using simplified fast r-CNN. International Workshop on Advanced Image Technology (IWAIT) 2018:1\u20133. https:\/\/doi.org\/10.1109\/IWAIT.2018.8369767","journal-title":"International Workshop on Advanced Image Technology (IWAIT)"},{"key":"12422_CR12","doi-asserted-by":"publisher","unstructured":"Jazayeri A, Cai H, Zheng JY, Tuceryan M (2011) Vehicle Detection and Tracking in Car Video Based on Motion Model. In: IEEE Transactions on Intelligent Transportation Systems. https:\/\/doi.org\/10.1109\/TITS.2011.2113340, vol 12, pp 583\u2013595","DOI":"10.1109\/TITS.2011.2113340"},{"key":"12422_CR13","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1109\/IVS.2009.5164278","volume":"2009","author":"R Lin","year":"2009","unstructured":"Lin R, Cao X, Xu Y, Wu C, Qiao H (2009) Airborne moving vehicle detection for video surveillance of urban traffic. IEEE Intelligent Vehicles Symposium, Xi\u2019an 2009:203\u2013208. https:\/\/doi.org\/10.1109\/IVS.2009.5164278","journal-title":"IEEE Intelligent Vehicles Symposium, Xi\u2019an"},{"key":"12422_CR14","doi-asserted-by":"publisher","unstructured":"Li Y, Li B, Tian B, Yao Q (2013) Vehicle Detection Based on the and\u2013 or Graph for Congested Traffic Conditions. In: IEEE Transactions on Intelligent Transportation Systems. https:\/\/doi.org\/10.1109\/TITS.2013.2250501, vol 14, pp 984\u2013993","DOI":"10.1109\/TITS.2013.2250501"},{"key":"12422_CR15","doi-asserted-by":"crossref","unstructured":"Mansour A, Hassan A, Hussein WM, Said E (2019) Automated vehicle detection in satellite images using deep learning, IOP Conference series: Materials Science and Engineering, Vol. 610","DOI":"10.1088\/1757-899X\/610\/1\/012027"},{"key":"12422_CR16","doi-asserted-by":"publisher","unstructured":"Min W, Fan M, Guo X, Han Q (2018) A New Approach to Track Multiple Vehicles With the Combination of Robust Detection and Two Classifiers. In: IEEE Transactions on Intelligent Transportation Systems. https:\/\/doi.org\/10.1109\/TITS.2017.2756989, vol 19, pp 174\u2013186","DOI":"10.1109\/TITS.2017.2756989"},{"key":"12422_CR17","doi-asserted-by":"publisher","unstructured":"Satzoda RK, Trivedi MM (s2016) Multipart Vehicle Detection Using Symmetry-Derived Analysis and Active Learning. In: IEEE Transactions on Intelligent Transportation Systems. https:\/\/doi.org\/10.1109\/TITS.2015.2494586, vol 17, pp 926\u2013937","DOI":"10.1109\/TITS.2015.2494586"},{"key":"12422_CR18","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1186\/s12544-019-0390-4","volume":"11","author":"H Song","year":"2019","unstructured":"Song H, Liang H, Li H et al (2019) Vision-based vehicle detection and counting system using deep learning in highway scenes. Eur. Transp. Res. Rev. 11:51. https:\/\/doi.org\/10.1186\/s12544-019-0390-4","journal-title":"Eur. Transp. Res. Rev."},{"key":"12422_CR19","doi-asserted-by":"publisher","unstructured":"Stauffer C, Grimson WEL (1999) Adaptive background mixture models for real-time tracking, Proceedings. 1999. https:\/\/doi.org\/10.1109\/CVPR.1999.784637, vol 2, pp 246\u2013252","DOI":"10.1109\/CVPR.1999.784637"},{"key":"12422_CR20","doi-asserted-by":"publisher","unstructured":"Tian B, Li Y, Li B, Wen D (2014) Rear-View Vehicle Detection and Tracking by Combining Multiple Parts for Complex Urban Surveillance. In: IEEE Transactions on Intelligent Transportation Systems. https:\/\/doi.org\/10.1109\/TITS.2013.2283302, vol 15, pp 597\u2013606","DOI":"10.1109\/TITS.2013.2283302"},{"key":"12422_CR21","unstructured":"Wiedemann C, Heipke C, Mayer H, Jamet O (1998) Empirical evaluation of automatically extracted road axes. In: Empirical evaluation methods in computer vision, k. Bowyer and p. phillips, Eds. IEEE Comput. Soc. Press, New York, pp 172\u2013187"},{"key":"12422_CR22","doi-asserted-by":"crossref","unstructured":"Yamazaki F, Liu W, Vu TT (2008) Vehicle extraction and speed detection from digital aerial images. In: IGARSS 2008\u20132008 IEEE International Geoscience and Remote Sensing Symposium, Boston, MA, pp. III-1334\u2013III-1337","DOI":"10.1109\/IGARSS.2008.4779606"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-12422-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-12422-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-12422-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,23]],"date-time":"2022-07-23T07:13:14Z","timestamp":1658560394000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-12422-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,31]]},"references-count":22,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["12422"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-12422-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,31]]},"assertion":[{"value":"27 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 May 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 January 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 March 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}