{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:18:45Z","timestamp":1761743925042,"version":"build-2065373602"},"reference-count":17,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2014,4,10]],"date-time":"2014-04-10T00:00:00Z","timestamp":1397088000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper investigates the robustness of a new thermal-infrared pedestrian detection system under different outdoor environmental conditions. In first place the algorithm for pedestrian ROI extraction in thermal-infrared video based on both thermal and motion information is introduced. Then, the evaluation of the proposal is detailed after describing the complete thermal and motion information fusion. In this sense, the environment chosen for evaluation is described, and the twelve test sequences are specified. For each of the sequences captured from a forward-looking infrared FLIR A-320 camera, the paper explains the weather and light conditions under which it was captured. The results allow us to draw firm conclusions about the conditions under which it can be affirmed that it is efficient to use our thermal-infrared proposal to robustly extract  human ROIs.<\/jats:p>","DOI":"10.3390\/s140406666","type":"journal-article","created":{"date-parts":[[2014,4,10]],"date-time":"2014-04-10T11:41:08Z","timestamp":1397130068000},"page":"6666-6676","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Thermal-Infrared Pedestrian ROI Extraction through Thermal and Motion Information Fusion"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8211-0398","authenticated-orcid":false,"given":"Antonio","family":"Fern\u00e1ndez-Caballero","sequence":"first","affiliation":[{"name":"Departamento de Sistemas Inform\u00e1ticos, Universidad de Castilla-La Mancha, 02071-Albacete, Spain"},{"name":"Instituto de Investigaci\u00f3n en Inform\u00e1tica de Albacete, 02071-Albacete, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mar\u00eda","family":"L\u00f3pez","sequence":"additional","affiliation":[{"name":"Departamento de Sistemas Inform\u00e1ticos, Universidad de Castilla-La Mancha, 02071-Albacete, Spain"},{"name":"Instituto de Investigaci\u00f3n en Inform\u00e1tica de Albacete, 02071-Albacete, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Serrano-Cuerda","sequence":"additional","affiliation":[{"name":"Instituto de Investigaci\u00f3n en Inform\u00e1tica de Albacete, 02071-Albacete, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,4,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1109\/TPAMI.2011.155","article-title":"Pedestrian detection: An evaluation of the state of the art","volume":"34","author":"Wojek","year":"2012","journal-title":"IEEE Trans. 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