{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:01:43Z","timestamp":1760238103059,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2020,7,17]],"date-time":"2020-07-17T00:00:00Z","timestamp":1594944000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020","doi-asserted-by":"publisher","award":["833704","787120"],"award-info":[{"award-number":["833704","787120"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Face recognition systems face real challenges from various presentation attacks. New, more sophisticated methods of presentation attacks are becoming more difficult to detect using traditional face recognition systems. Thermal infrared imaging offers specific physical properties that may boost presentation attack detection capabilities. The aim of this paper is to present outcomes of investigations on the detection of various face presentation attacks in thermal infrared in various conditions including thermal heating of masks and various states of subjects. A thorough analysis of presentation attacks using printed and displayed facial photographs, 3D-printed, custom flexible 3D-latex and silicone masks is provided. The paper presents the intensity analysis of thermal energy distribution for specific facial landmarks during long-lasting experiments. Thermalization impact, as well as varying the subject\u2019s state due to physical effort on presentation attack detection are investigated. A new thermal face spoofing dataset is introduced. Finally, a two-step deep learning-based method for the detection of presentation attacks is presented. Validation results of a set of deep learning methods across various presentation attack instruments are presented.<\/jats:p>","DOI":"10.3390\/s20143988","type":"journal-article","created":{"date-parts":[[2020,7,17]],"date-time":"2020-07-17T10:22:02Z","timestamp":1594981322000},"page":"3988","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A Study on Presentation Attack Detection in Thermal Infrared"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1361-9828","authenticated-orcid":false,"given":"Marcin","family":"Kowalski","sequence":"first","affiliation":[{"name":"Institute of Optoelectronics, Military University of Technology, 2 Gen. S. Kaliskiego St., 00-908 Warsaw, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,17]]},"reference":[{"key":"ref_1","unstructured":"ITTF (2016). ISO\/IEC 30107-1:2016 Information Technology\u2014Biometric Presentation Attack Detection\u2014Part 1, Information Technology Task Force (ITTF)."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tan, X., Li, Y., Liu, J., and Jiang, L. (2010, January 5\u201311). Face liveness detection from a single image with sparse low rank bilinear discriminative model. Proceedings of the European Conference on Computer Vision, Crete, Greece.","DOI":"10.1007\/978-3-642-15567-3_37"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pan, G., Sun, L., Wu, Z., and Lao, S. (2007, January 14\u201320). Eyeblink-Based Anti-Spoofing in Face Recognition from a Generic Webcamera. 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