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The proposed model exploits three different input modalities: RGB imagery, thermographic imagery and Channel State Information from Wi-Fi signal reflectance to estimate human intrusion and suspicious activity. The fused multimodal information is used as input in a Bidirectional LSTM, which has the benefit of being able to capture temporal interdependencies in both past and future time instances, a significant aspect in the discussed unusual activity detection scenario. We also present a Bayesian optimization framework that fine-tunes the Bidirectional LSTM parameters in an optimal manner. The proposed framework is evaluated on real-world data from a critical water infrastructure protection and monitoring scenario and the results indicate a superior performance compared to other unimodal and multimodal approaches and classification models.<\/jats:p>","DOI":"10.1007\/978-3-030-69781-5_6","type":"book-chapter","created":{"date-parts":[[2021,2,19]],"date-time":"2021-02-19T11:12:22Z","timestamp":1613733142000},"page":"77-86","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Fusing RGB and Thermal Imagery with Channel State Information for Abnormal Activity Detection Using Multimodal Bidirectional LSTM"],"prefix":"10.1007","author":[{"given":"Nikolaos","family":"Bakalos","sequence":"first","affiliation":[]},{"given":"Athanasios","family":"Voulodimos","sequence":"additional","affiliation":[]},{"given":"Nikolaos","family":"Doulamis","sequence":"additional","affiliation":[]},{"given":"Anastasios","family":"Doulamis","sequence":"additional","affiliation":[]},{"given":"Kassiani","family":"Papasotiriou","sequence":"additional","affiliation":[]},{"given":"Matthaios","family":"Bimpas","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,2,18]]},"reference":[{"key":"6_CR1","doi-asserted-by":"crossref","unstructured":"Co\u015far, S., Donatiello, G., Bogorny, V., Garate, C., Alvares, L.O., Br\u00e9mond, F.: Toward abnormal trajectory and event detection in video surveillance. 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