[en] Biometrics has become a popular field for the development of techniques that aim at recognizing humans based upon one or more intrinsic physical or behavioral traits. In particular, many solutions dedicated to access control integrate biometric features like fingerprinting or face recognition.
This paper describes a new method designed to interpret what happens when crossing an invisible vertical plane, called virtual curtain hereafter, at the footstep of a door frame. It relies on the use of two laser scanners located in the upper corners of the frame, and on the classification of the time series of the information provided by the scanners after registration. The technique is trained and tested on a set of sequences representative for multiple scenarios of normal crossings by a single person and for tentatives to fool the system.
We present the details of the technique and discuss classification results. It appears that the technique is capable to recognize many scenarios which may lead to the development of new commercial applications.
Centre/Unité de recherche :
Intelsig Telim
Disciplines :
Ingénierie électrique & électronique
Auteur, co-auteur :
Barnich, Olivier
Pierard, Sébastien ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications
Van Droogenbroeck, Marc ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications
Langue du document :
Anglais
Titre :
A virtual curtain for the detection of humans and access control
Date de publication/diffusion :
décembre 2010
Nom de la manifestation :
Advanced Concepts for Intelligent Vision Systems (ACIVS 2010)
Lieu de la manifestation :
Sydney, Australie
Date de la manifestation :
December
Manifestation à portée :
International
Titre de l'ouvrage principal :
Advanced Concepts for Intelligent Vision Systems (ACIVS)
Pagination :
98-109
Peer review/Comité de sélection :
Peer reviewed
Organisme subsidiant :
BEA s.a. ( http://www.bea.be )
Commentaire :
This work was supported by BEA s.a. ( http://www.bea.be ).
Jain, A., Flynn, P., Ross, A.: Handbook of Biometrics. Springer, Heidelberg (2008)
Sequeira, V., Boström, G.: Gonçalves, J.: 3D site modelling and verification: usage of 3D laser techniques for verification of plant design for nuclear security applications. In: Koschan, A., Pollefeys, M., Abidi, M. (eds.) 3D Imaging for Safety and Security, pp. 225-247. Springer, Heidelberg (2007)
Boulgouris, N., Hatzinakos, D., Plataniotis, K.: Gait recognition: a challenging signal processing technology for biometric identification. IEEE Signal Processing Magazine 22(6), 78-90 (2005) (Pubitemid 46404905)
Nixon, M., Carter, J., Shutler, J., Grant, M.: New advances in automatic gait recognition. Elsevier Information Security Technical Report 7(4), 23-35 (2002)
Nixon, M., Tan, T., Chellappa, R.: Human identification based on gait. Springer, Heidelberg (2006)
Foster, J., Nixon, M., Prügel-Bennett, A.: Automatic gait recognition using areabased metrics. Pattern Recognition Letters 24(14), 2489-2497 (2003)
Huang, X., Boulgouris, N.: Human gait recognition based on multiview gait sequences. EURASIP Journal on Advances in Signal Processing, 8 (January 2008)
Wang, L., Tan, T., Ning, H., Hu, W.: Silhouette analysis-based gait recognition for human identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1505-1518 (2003)
Soriano, M., Araullo, A., Saloma, C.: Curve spreads: a biometric from front-view gait video. Pattern Recognition Letters 25(14), 1595-1602 (2004)
Boulgouris, N., Chi, Z.: Gait recognition using radon transform and linear discriminant analysis. IEEE Transactions on Image Processing 16(3), 731-740 (2007)
Kale, A., Cuntoor, N., Yegnanarayana, B., Rajagopalan, A., Chellappa, R.: Gait analysis for human identification. In: Proceedings of the International Conference on Audio-and Video-Based Person Authentication, Guildford, UK, pp. 706-714 (2003)
Liu, Y., Collins, R., Tsin, Y.: Gait sequence analysis using frieze patterns. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2351, pp. 657-671. Springer, Heidelberg (2002)
Lee, S., Liu, Y., Collins, R.: Shape variation-based frieze pattern for robust gait recognition. In: IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1-8 (June 2007)
Barnich, O., Jodogne, S., Van Droogenbroeck, M.: Robust analysis of silhouettes by morphological size distributions. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2006. LNCS, vol. 4179, pp. 734-745. Springer, Heidelberg (2006)
Barnich, O., Van Droogenbroeck, M.: Frontal-view gait recognition by intra- and inter-frame rectangle size distribution. Pattern Recognition Letters 30(10), 893-901 (2009)
Boulgouris, N., Plataniotis, K., Hatzinakos, D.: Gait recognition using linear time normalization. Pattern Recognition 39(5), 969-979 (2006)