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Thanks to the spread of smart cameras, video fire detection is gaining more attention as a solution to monitor wide outdoor areas where no specific sensors for smoke detection are available. However, state-of-the-art fire detectors assure a satisfactory Recall but exhibit a high false-positive rate that renders the application practically unusable. In this paper, we propose FLAME, an efficient and adaptive classification framework to address fire detection from videos. The framework integrates a state-of-the-art deep neural network for frame-wise object detection, in an automatic video analysis tool. The advantages of our approach are twofold. On the one side, we exploit advances in image detector technology to ensure a high Recall. On the other side, we design a model-based motion analysis that improves the system\u2019s Precision by filtering out fire candidates occurring in the scene\u2019s background or whose movements differ from those of the fire. The proposed technique, able to be executed in real-time on embedded systems, has proven to surpass the methods considered for comparison on a recent literature dataset representing several scenarios. The code and the dataset used for designing the system have been made publicly available by the authors at (<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/mivia.unisa.it\/large-fire-dataset-with-negative-samples-lfdn\/\" ext-link-type=\"uri\">https:\/\/mivia.unisa.it\/large-fire-dataset-with-negative-samples-lfdn\/<\/jats:ext-link>).<\/jats:p>","DOI":"10.1007\/s00521-024-10963-z","type":"journal-article","created":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T04:02:44Z","timestamp":1736395364000},"page":"6181-6197","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["FLAME: fire detection in videos combining a deep neural network with a model-based motion analysis"],"prefix":"10.1007","volume":"37","author":[{"given":"Diego","family":"Gragnaniello","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5495-2432","authenticated-orcid":false,"given":"Antonio","family":"Greco","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlo","family":"Sansone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruno","family":"Vento","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,9]]},"reference":[{"issue":"11","key":"10963_CR1","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1038\/s41577-022-00776-3","volume":"22","author":"CA Akdis","year":"2022","unstructured":"Akdis CA, Nadeau KC (2022) Human and planetary health on fire. 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