{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T18:16:30Z","timestamp":1780424190509,"version":"3.54.1"},"reference-count":56,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,10,24]],"date-time":"2019-10-24T00:00:00Z","timestamp":1571875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>With the consolidation of the new data protection regulation paradigm for each individual within the European Union (EU), major biometric technologies are now confronted with many concerns related to user privacy in biometric deployments. When individual biometrics are disclosed, the sensitive information about his\/her personal data such as financial or health are at high risk of being misused or compromised. This issue can be escalated considerably over scenarios of non-cooperative users, such as elderly people residing in care homes, with their inability to interact conveniently and securely with the biometric system. The primary goal of this study is to design a novel database to investigate the problem of automatic people recognition under privacy constraints. To do so, the collected data-set contains the subject\u2019s hand and foot traits and excludes the face biometrics of individuals in order to protect their privacy. We carried out extensive simulations using different baseline methods, including deep learning. Simulation results show that, with the spatial features extracted from the subject sequence in both individual hand or foot videos, state-of-the-art deep models provide promising recognition performance.<\/jats:p>","DOI":"10.3390\/e21111033","type":"journal-article","created":{"date-parts":[[2019,10,25]],"date-time":"2019-10-25T04:41:27Z","timestamp":1571978487000},"page":"1033","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Privacy-Constrained Biometric System for Non-Cooperative Users"],"prefix":"10.3390","volume":"21","author":[{"given":"Mohammad N.","family":"S. Jahromi","sequence":"first","affiliation":[{"name":"Visual Analysis of People Laboratory, Aalborg University, 9100 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pau","family":"Buch-Cardona","sequence":"additional","affiliation":[{"name":"Computer Vision Centre, Universitat Aut\u00f2noma de Barcelona, 08193 Bellaterra (Cerdanyola), Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Egils","family":"Avots","sequence":"additional","affiliation":[{"name":"iCV Lab, Institute of Technology, University of Tartu, 50411 Tartu, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kamal","family":"Nasrollahi","sequence":"additional","affiliation":[{"name":"Visual Analysis of People Laboratory, Aalborg University, 9100 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0617-8873","authenticated-orcid":false,"given":"Sergio","family":"Escalera","sequence":"additional","affiliation":[{"name":"Computer Vision Centre, Universitat Aut\u00f2noma de Barcelona, 08193 Bellaterra (Cerdanyola), Barcelona, Spain"},{"name":"Department of Mathematics and Informatics, Universitat de Barcelona, 08007 Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas B.","family":"Moeslund","sequence":"additional","affiliation":[{"name":"Visual Analysis of People Laboratory, Aalborg University, 9100 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8460-5717","authenticated-orcid":false,"given":"Gholamreza","family":"Anbarjafari","sequence":"additional","affiliation":[{"name":"iCV Lab, Institute of Technology, University of Tartu, 50411 Tartu, Estonia"},{"name":"Department of Electrical and Electronic Engineering, Hasan Kalyoncu University, 27900 Gaziantep, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Crisan, S. (2017). A Novel Perspective on Hand Vein Patterns for Biometric Recognition: Problems, Challenges, and Implementations. Biometric Security and Privacy, Springer.","DOI":"10.1007\/978-3-319-47301-7_2"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11042-019-7667-4","article-title":"A novel deep network architecture for reconstructing RGB facial images from thermal for face recognition","volume":"78","author":"Litvin","year":"2019","journal-title":"Multimed. Tools Appl."},{"key":"ref_3","unstructured":"Leyvand, T., Li, J., Meekhof, C., Keosababian, T., Stachniak, S., Gunn, R., Stuart, A., Glaser, R., Mays, E., and Huynh, T. (2017). Biometric recognition. (9,539,500), U.S. Patent."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Rath, A., Spasic, B., Boucart, N., and Thiran, P. (2019). Security Pattern for Cloud SaaS: From System and Data Security to Privacy Case Study in AWS and Azure. Computers, 8.","DOI":"10.3390\/computers8020034"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Campisi, P. (2013). Security and Privacy in Biometrics, Springer.","DOI":"10.1007\/978-1-4471-5230-9"},{"key":"ref_6","unstructured":"Regulation Protection (2019, October 23). Regulation (EU) 2016\/679 of the European Parliament and of the Council, April 2016. Available online: http:\/\/www.gkdm.co.il\/wp-content\/uploads\/2018\/02\/GDPR-Israel.pdf."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ofodile, I., Helmi, A., Clap\u00e9s, A., Avots, E., Peensoo, K.M., Valdma, S.M., Valdmann, A., Valtna-Lukner, H., Omelkov, S., and Escalera, S. (2019). Action Recognition Using Single-Pixel Time-of-Flight Detection. Entropy, 21.","DOI":"10.3390\/e21040414"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Sapi\u0144ski, T., Kami\u0144ska, D., Pelikant, A., and Anbarjafari, G. (2019). Emotion recognition from skeletal movements. Entropy, 21.","DOI":"10.3390\/e21070646"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Sabet Jahromi, M.N., Bonderup, M.B., Asadi, M., Avots, E., Nasrollahi, K., Escalera, S., Kasaei, S., Moeslund, T., and Anbarjafari, G. (2018, January 7). Automatic Access Control Based on Face and Hand Biometrics in A Non-Cooperative Context. Proceedings of the IEEE Winter Conference on Applications of Computer Vision - Cross Domain Biometric Recognition Workshop, Hawaii, HI, USA.","DOI":"10.1109\/WACVW.2018.00009"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Ishihara, T., Kitani, K.M., Ma, W.C., Takagi, H., and Asakawa, C. (2015, January 27\u201330). Recognizing hand-object interactions in wearable camera videos. Proceedings of the IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada.","DOI":"10.1109\/ICIP.2015.7351020"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.1109\/TCSVT.2015.2469551","article-title":"Survey on 3D hand gesture recognition","volume":"26","author":"Cheng","year":"2016","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2797","DOI":"10.1016\/j.patcog.2009.02.007","article-title":"A survey of biometric technology based on hand shape","volume":"42","author":"Duta","year":"2001","journal-title":"Pattern Recognit."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/34.910878","article-title":"The recognition of human movement using temporal templates","volume":"23","author":"Bobick","year":"2001","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1478","DOI":"10.1016\/j.patrec.2006.02.021","article-title":"Personal authentication using hand images","volume":"27","author":"Kumar","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_15","unstructured":"Amayeh, G., Bebis, G., Erol, A., and Nicolescu, M. (2006, January 17\u201322). Peg-free hand shape verification using high order Zernike moments. Proceedings of the Conference on Computer Vision and Pattern Recognition Workshop, CVPRW\u201906, New York, NY, USA."},{"key":"ref_16","first-page":"12","article-title":"Personal authentication using hand-geometry and palmprint features\u2013The state of the art","volume":"11","year":"2004","journal-title":"Hand"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"20525","DOI":"10.1007\/s11042-016-3988-8","article-title":"Fusing shape and spatio-temporal features for depth-based dynamic hand gesture recognition","volume":"76","author":"Zheng","year":"2017","journal-title":"Multimed. Tools Appl."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1016\/j.eswa.2006.10.032","article-title":"Hand geometry identification without feature extraction by general regression neural network","volume":"34","author":"Polat","year":"2008","journal-title":"Expert Syst. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.inffus.2015.06.007","article-title":"Group sparse representation based classification for multi-feature multimodal biometrics","volume":"32","author":"Goswami","year":"2016","journal-title":"Inf. Fusion"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2127","DOI":"10.1109\/TIP.2009.2023153","article-title":"Personal authentication using hand vein triangulation and knuckle shape","volume":"18","author":"Kumar","year":"2009","journal-title":"IEEE Trans. Image Process."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Malutan, R., Emerich, S., Crisan, S., Pop, O., and Lefkovits, L. (2017, January 6\u20138). Dorsal hand vein recognition based on Riesz Wavelet Transform and Local Line Binary Pattern. Proceedings of the 3rd International Conference on Frontiers of Signal Processing (ICFSP), Paris, France.","DOI":"10.1109\/ICFSP.2017.8097159"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s11760-012-0422-1","article-title":"Video resolution enhancement by using discrete and stationary wavelet transforms with illumination compensation","volume":"9","author":"Anbarjafari","year":"2015","journal-title":"Signal Image Video Process."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Li, X., Huang, D., and Wang, Y. (2016, January 14\u201316). Comparative study of deep learning methods on dorsal hand vein recognition. Proceedings of the Chinese Conference on Biometric Recognition, Chengdu, China.","DOI":"10.1007\/978-3-319-46654-5_33"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1816","DOI":"10.1109\/TIFS.2017.2689724","article-title":"Deep representation-based feature extraction and recovering for finger-vein verification","volume":"12","author":"Qin","year":"2017","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wang, L., and Leedham, G. (2005, January 22\u201325). A thermal hand vein pattern verification system. Proceedings of the International Conference on Pattern Recognition and Image Analysis, Bath, UK.","DOI":"10.1007\/11552499_7"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1016\/j.patcog.2007.07.012","article-title":"Minutiae feature analysis for infrared hand vein pattern biometrics","volume":"41","author":"Wang","year":"2008","journal-title":"Pattern Recognit."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.neucom.2012.08.038","article-title":"A sparse representation method of bimodal biometrics and palmprint recognition experiments","volume":"103","author":"Xu","year":"2013","journal-title":"Neurocomputing"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wan, H., Chen, L., Song, H., and Yang, J. (2017, January 13\u201316). Dorsal hand vein recognition based on convolutional neural networks. Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, USA.","DOI":"10.1109\/BIBM.2017.8217830"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/0379-0738(96)01969-X","article-title":"Uniqueness of bare feet and its use as a possible means of identification","volume":"82","author":"Kennedy","year":"1996","journal-title":"Forensic Sci. Int."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"011016","DOI":"10.1117\/1.2892674","article-title":"Footprint-based biometric verification","volume":"17","author":"Uhl","year":"2008","journal-title":"J. Electron. Imaging"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1534","DOI":"10.1109\/10.880106","article-title":"Footprint-based personal recognition","volume":"47","author":"Nakajima","year":"2000","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_32","unstructured":"Jung, J.W., Bien, Z., Lee, S.W., and Sato, T. (2003, January 17\u201321). Dynamic-footprint based person identification using mat-type pressure sensor. Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No. 03CH37439), Cancun, Mexico."},{"key":"ref_33","first-page":"774","article-title":"Employment of footprint recognition system","volume":"3","author":"Kumar","year":"2013","journal-title":"Indian J. Comput. Sci. Eng. (IJCSE)"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1177\/002580249803800411","article-title":"Predictive value of human footprints in a forensic context","volume":"38","author":"Barker","year":"1998","journal-title":"Med. Sci. Law"},{"key":"ref_35","first-page":"28","article-title":"Manifold feature extraction for foot print image","volume":"1","author":"Kumar","year":"2012","journal-title":"Indian J. Bioinform. Biotechnol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Kushwaha, R., Nain, N., and Singal, G. (2017, January 4\u20137). Detailed analysis of footprint geometry for person identification. Proceedings of the 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Jaipur, India.","DOI":"10.1109\/SITIS.2017.47"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Rohit Khokher, R.C.S. (2016). Footprint-based personal recognition using scanning technique. Indian J. Sci. Technol., 9.","DOI":"10.17485\/ijst\/2016\/v9i44\/105167"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Boyd, J.E., and Little, J.J. (2005). Biometric gait recognition. Advanced Studies in Biometrics, Springer.","DOI":"10.1007\/11493648_2"},{"key":"ref_39","unstructured":"MathWorks (2019, October 23). Single Camera Calibrator App. Available online: https:\/\/www.mathworks.com\/help\/vision\/ug\/single-camera-calibrator-app.html."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Ahonen, T., Hadid, A., and Pietik\u00e4inen, M. (2004, January 11\u201314). Face recognition with local binary patterns. Proceedings of the European Conference on Computer Vision, Prague, Czech Republic.","DOI":"10.1007\/978-3-540-24670-1_36"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2037","DOI":"10.1109\/TPAMI.2006.244","article-title":"Face description with local binary patterns: Application to face recognition","volume":"28","author":"Ahonen","year":"2006","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1155\/2009\/482585","article-title":"Data fusion boosted face recognition based on probability distribution functions in different colour channels","volume":"2009","author":"Demirel","year":"2009","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Benzaoui, A., Boukrouche, A., Doghmane, H., and Bourouba, H. (2015, January 25\u201327). Face recognition using 1DLBP, DWT and SVM. Proceedings of the 3rd International Conference on Control, Engineering & Information Technology (CEIT), Tlemcen, Algeria.","DOI":"10.1109\/CEIT.2015.7233002"},{"key":"ref_44","unstructured":"Drucker, H., Burges, C.J., Kaufman, L., Smola, A.J., and Vapnik, V. (1997, January 3\u20135). Support vector regression machines. Proceedings of the 9th International Conference on Neural Information Processing Systems, Denver, CO, USA."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lkopf, B., Burges, C., and Vapnik, V. (1996, January 16\u201319). Incorporating invariances in support vector learning machines. Proceedings of the International Conference on Artificial Neural Networks, Bochum, Germany.","DOI":"10.1007\/3-540-61510-5_12"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Elshatoury, H., Avots, E., Anbarjafari, G., and Initiative, A.D.N. (2019, October 23). Volumetric Histogram-Based Alzheimer\u2019s Disease Detection Using Support Vector Machine. Available online: https:\/\/content.iospress.com\/articles\/journal-of-alzheimers-disease\/jad190704.","DOI":"10.3233\/JAD-190704"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Cherifi, D., Cherfaoui, F., Yacini, S.N., and Nait-Ali, A. (2016, January 4\u20137). Fusion of face recognition methods at score level. Proceedings of the International Conference on Bio-engineering for Smart Technologies (BioSMART), Dubai, UAE.","DOI":"10.1109\/BIOSMART.2016.7835458"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","article-title":"Multiresolution gray-scale and rotation invariant texture classification with local binary patterns","volume":"24","author":"Ojala","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1109\/JPROC.2010.2044470","article-title":"Sparse representation for computer vision and pattern recognition","volume":"98","author":"Wright","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Li, X., Jia, T., and Zhang, H. (2009, January 20\u201325). Expression-insensitive 3D face recognition using sparse representation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA.","DOI":"10.1109\/CVPR.2009.5206613"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Mairal, J., Bach, F., Ponce, J., Sapiro, G., and Zisserman, A. (2008). Discriminative Learned Dictionaries for Local Image Analysis, Minnesota Univ. Minneapolis Inst. for Mathematics and Its Applications.","DOI":"10.1109\/CVPR.2008.4587652"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Cai, J.F., Ji, H., Liu, C., and Shen, Z. (2009, January 20\u201325). Blind motion deblurring from a single image using sparse approximation. Proceedings of the Conference on Computer Vision and Pattern Recognition, Miami, FL, USA.","DOI":"10.1109\/CVPR.2009.5206743"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhang, Q., and Li, B. (2010, January 13\u201318). Discriminative K-SVD for dictionary learning in face recognition. Proceedings of the Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5539989"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1109\/34.387503","article-title":"Recursive estimation of motion, structure, and focal length","volume":"6","author":"Azarbayejani","year":"1995","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_55","unstructured":"Krizhevsky, A., Sutskever, I., and Hinton, G.E. (2012, January 3\u20138). Imagenet classification with deep convolutional neural networks. Proceedings of the Neural Information Processing Systems Conference, Lake Tahoe, NV, USA."},{"key":"ref_56","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J. (July, January 26). Deep residual learning for image recognition. Proceedings of the Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/11\/1033\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:29:04Z","timestamp":1760189344000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/11\/1033"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,24]]},"references-count":56,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["e21111033"],"URL":"https:\/\/doi.org\/10.3390\/e21111033","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,24]]}}}