{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T16:41:17Z","timestamp":1776012077424,"version":"3.50.1"},"reference-count":26,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2016,1,27]],"date-time":"2016-01-27T00:00:00Z","timestamp":1453852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Gender information has many useful applications in computer vision systems, such as surveillance systems, counting the number of males and females in a shopping mall, accessing control systems in restricted areas, or any human-computer interaction system. In most previous studies, researchers attempted to recognize gender by using visible light images of the human face or body. However, shadow, illumination, and time of day greatly affect the performance of these methods. To overcome this problem, we propose a new gender recognition method based on the combination of visible light and thermal camera images of the human body. Experimental results, through various kinds of feature extraction and fusion methods, show that our approach is efficient for gender recognition through a comparison of recognition rates with conventional systems.<\/jats:p>","DOI":"10.3390\/s16020156","type":"journal-article","created":{"date-parts":[[2016,1,28]],"date-time":"2016-01-28T02:19:45Z","timestamp":1453947585000},"page":"156","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Body-Based Gender Recognition Using Images from Visible and Thermal Cameras"],"prefix":"10.3390","volume":"16","author":[{"given":"Dat","family":"Nguyen","sequence":"first","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30, Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kang","family":"Park","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 30, Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,1,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/978-3-642-32695-0_31","article-title":"Recognizing human gender in computer vision: A survey","volume":"7458","author":"Ng","year":"2012","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_2","unstructured":"Lu, L., Xu, Z., and Shi, P. (April, January 31). Gender Classification of Facial Images Based on Multiple Facial Regions. Proceedings the World Congress on Computer Science and Information Engineering, Los Angeles, CA, USA."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1007\/978-3-642-12297-2_23","article-title":"Gender from body: A biologically-inspired approach with manifold learning","volume":"5996","author":"Guo","year":"2009","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ichino, M., Komatsu, N., Wang, J.-G., and Yun, Y.W. (2010, January 7\u201310). Speaker Gender Recognition Using Score Level Fusion by Adaboost. Proceedings of the 11th International Conference on Control Automation Robotics and Vision, Singapore.","DOI":"10.1109\/ICARCV.2010.5707960"},{"key":"ref_5","unstructured":"Sloka, S., and Sridharan, S. (1997, January 4). Automatic Gender Identification Optimised for Language Independence. Proceedings of the IEEE Annual Conference on Speech and Image Technologies for Computing and Telecommunications, Brisbane, Australia."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Arun, K.S., and Rarath, K.S. (2011, January 22\u201324). A Machine Learning Approach for Fingerprint Based Gender Identification. Proceedings of IEEE Conference on Recent Advances in Intelligent Computational Systems, Trivandrum, India.","DOI":"10.1109\/RAICS.2011.6069294"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.imavis.2013.11.001","article-title":"Face gender classification: A statistical study when neutral and distorted faces are combined for training and testing purposes","volume":"32","author":"Andreu","year":"2014","journal-title":"Image Vis. Comput."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.patrec.2013.04.028","article-title":"Robust gender recognition by exploiting facial attributes dependencies","volume":"36","author":"Buenaposada","year":"2014","journal-title":"Pattern Recognit. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2818","DOI":"10.1016\/j.patcog.2009.02.011","article-title":"Combining appearance and motion for face and gender recognition from videos","volume":"42","author":"Hadid","year":"2009","journal-title":"Pattern Recognit."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Li, X., Zhao, X., Fu, Y., and Liu, Y. (2010, January 13\u201318). Bimodal Gender Recognition from Face and Fingerprint. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5539969"},{"key":"ref_11","unstructured":"Xu, X.-Y., Yu, B., Wang, Z., and Yin, Z. (2013, January 26\u201327). A Multimodal Gender Recognition Based on Bayesian Hierarchical Model. Proceedings of the 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, China."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Cao, L., Dikmen, M., Fu, Y., and Huang, T.S. (,  2008). Gender Recognition from Body. Proceedings of the 16th ACM International Conference on Multimedia, New York, NY, USA.","DOI":"10.1145\/1459359.1459470"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1109\/TSMCC.2011.2104950","article-title":"Gender Recognition Using 3-D Body Shapes","volume":"41","author":"Tang","year":"2011","journal-title":"IEEE Trans. Syst. Man Cybern. Part C Appl. Rev."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Tang, J., Liu, X., Cheng, H., and Robinette, K.M. (2012, January 14\u201317). Gender Recognition with Limited Feature Points from 3-D Human Body Shapes. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, Seoul, Korea.","DOI":"10.1109\/ICSMC.2012.6378116"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"10580","DOI":"10.3390\/s150510580","article-title":"Robust pedestrian detection by combining visible and thermal infrared cameras","volume":"15","author":"Lee","year":"2015","journal-title":"Sensors"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"21898","DOI":"10.3390\/s150921898","article-title":"Human age estimation method robust to camera sensor and\/or face movement","volume":"15","author":"Nguyen","year":"2015","journal-title":"Sensors"},{"key":"ref_17","unstructured":"C600 Webcam Camera. Available online: https:\/\/support.logitech.com\/en_us\/product\/5869."},{"key":"ref_18","unstructured":"Tau2 Thermal Imaging Camera. Available: http:\/\/www.flir.com\/cores\/display\/?id=54717."},{"key":"ref_19","unstructured":"Dalal, N., and Triggs, B. (2005, January 25). Histogram of Oriented Gradients for Human Detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1401","DOI":"10.1016\/j.dsp.2013.04.001","article-title":"Fake finger-vein image detection based on fourier and wavelet transforms","volume":"23","author":"Nguyen","year":"2013","journal-title":"Digit. Signal. Prog."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"21726","DOI":"10.3390\/s141121726","article-title":"Face recognition system for set-top box-based intelligent TV","volume":"11","author":"Lee","year":"2014","journal-title":"Sensors"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/978-3-642-55038-6_67","article-title":"Human age estimation based on multi-level local binary pattern and regression method","volume":"309","author":"Nguyen","year":"2014","journal-title":"Lect. Notes Electr. Eng."},{"key":"ref_23","unstructured":"Torrisi, A., Farinella, G.M., Puglisi, G., and Battiato, S. (July, January 29). Selecting Discriminative CLBP Patterns for Age Estimation. Proceedings of the IEEE International Conference on Multimedia & Expo Workshops, Turin, Italy."},{"key":"ref_24","unstructured":"Santarcangelo, V., Farinella, G.M., and Battiato, S. (July, January 29). Gender Recognition: Methods, Dataset and Results. Proceedings of the IEEE International Conference on Multimedia & Expo Workshops, Turin, Italy."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1007\/978-3-319-12811-5_3","article-title":"Face re-identification for digital signage applications","volume":"8811","author":"Farinella","year":"2014","journal-title":"Lect. Notes. Compt. Sci."},{"key":"ref_26","unstructured":"OpenCV Library. Available online: http:\/\/opencv.org\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/2\/156\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:18:21Z","timestamp":1760210301000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/2\/156"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,27]]},"references-count":26,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2016,2]]}},"alternative-id":["s16020156"],"URL":"https:\/\/doi.org\/10.3390\/s16020156","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,27]]}}}