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Several offline approaches have been proposed to address this task; however, they are not compatible with real-world applications due to their high latency and post-processing requirements. This lack of suitable approaches motivates our proposal: A new low-latency online approach for MTMC tracking in scenarios with partially overlapping fields of view (FOVs), such as road intersections. Firstly, the proposed approach detects vehicles at each camera. Then, the detections are merged between cameras by applying cross-camera clustering based on appearance and location. Lastly, the clusters containing different detections of the same vehicle are temporally associated to compute the tracks on a frame-by-frame basis. The experiments show promising low-latency results while addressing real-world challenges such as the a priori unknown and time-varying number of targets and the continuous state estimation of them without performing any post-processing of the trajectories. Our code is available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/www-vpu.eps.uam.es\/publications\/Online-MTMC-Tracking\">http:\/\/www-vpu.eps.uam.es\/publications\/Online-MTMC-Tracking<\/jats:ext-link>.<\/jats:p>","DOI":"10.1007\/s11042-022-11923-2","type":"journal-article","created":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T14:02:49Z","timestamp":1643032969000},"page":"7063-7083","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Online clustering-based multi-camera vehicle tracking in scenarios with overlapping FOVs"],"prefix":"10.1007","volume":"81","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7961-2848","authenticated-orcid":false,"given":"Elena","family":"Luna","sequence":"first","affiliation":[]},{"given":"Juan C.","family":"SanMiguel","sequence":"additional","affiliation":[]},{"given":"Jos\u00e9 M.","family":"Mart\u00ednez","sequence":"additional","affiliation":[]},{"given":"Marcos","family":"Escudero-Vi\u00f1olo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,24]]},"reference":[{"key":"11923_CR1","unstructured":"Chang MC, Wei J, Zhu ZA, Chen Y, Hu CS, Jiang M, Chiang CK (2019) Ai city challenge 2019 \u2013 city-scale video analytics for smart transportation. 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SanMiguel, Jos\u00e9 M. Mart\u00ednez and Marcos Escudero-Vi\u00f1olo declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}