Abstract
This paper introduces the Gait Gate as the first online walk-through access control system based on multimodal biometric person verification. Face, gait and height modalities are simultaneously captured by a single RGB-D sensor and fused at the matching-score level. To achieve the real-time requirements, mutual subspace method has been used for the face matcher. An acceptance threshold has been learned beforehand using data of a set of subjects disjoint from the targets. The Gait Gate has been evaluated through experiments in actual online situation. In experiments, 1324 walking sequences have resulted from the verification of 26 targets. The verification results show an average computation time of less than 13 ms and an accuracy of 6.08% FAR and 7.21% FRR.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Safran Identity and Security: The worlds fastest contactless fingerprint scanner (2014). http://www.morpho.com
SRI International: Identity on the move walk-through identity reader (2016). https://www.sri.com/engage/products-solutions/iom-portal-system
Abate, A.F., Nappi, M., Riccio, D., Sabatino, G.: 2D and 3D face recognition: a survey. Pattern Recogn. Lett. 28, 1885–1906 (2007)
Jafri, R., Arabnia, H.R.: A survey of face recognition techniques. JIPS 5, 41–68 (2009)
Gross, R., Matthews, I., Cohn, J., Kanade, T., Baker, S.: Multi-PIE. Image Vis. Comput. 28, 807–813 (2010)
Nixon, M.S., Tan, T., Chellappa, R.: Human Identification Based on Gait, vol. 4. Springer Science & Business Media, Heidelberg (2010)
Kusakunniran, W., Wu, Q., Zhang, J., Li, H.: Gait recognition under various viewing angles based on correlated motion regression. IEEE Trans. Circuits Syst. Video Technol. 22, 966–980 (2012)
Makihara, Y., Sagawa, R., Mukaigawa, Y., Echigo, T., Yagi, Y.: Gait recognition using a view transformation model in the frequency domain. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3953, pp. 151–163. Springer, Heidelberg (2006). doi:10.1007/11744078_12
Makihara, Y., Tsuji, A., Yagi, Y.: Silhouette transformation based on walking speed for gait identification. In: Proceedings of the 23rd IEEE Conference on Computer Vision and Pattern Recognition, pp. 717–722 (2010)
Hossain, M.A., Makihara, Y., Wang, J., Yagi, Y.: Clothing-invariant gait identification using part-based clothing categorization and adaptive weight control. Pattern Recogn. 43, 2281–2291 (2010)
Shakhnarovich, G., Darrell, T.: On probabilistic combination of face and gait cues for identification. In: Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 169–174. IEEE (2002)
Kale, A., RoyChowdhury, A.K., Chellappa, R.: Fusion of gait and face for human identification. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2004), vol. 5, p. V-901. IEEE (2004)
Zhang, T., Li, X., Tao, D., Yang, J.: Multimodal biometrics using geometry preserving projections. Pattern Recogn. 41, 805–813 (2008)
Zhou, X., Bhanu, B.: Feature fusion of side face and gait for video-based human identification. Pattern Recogn. 41, 778–795 (2008)
Hofmann, M., Schmidt, S.M., Rajagopalan, A.N., Rigoll, G.: Combined face and gait recognition using alpha matte preprocessing. In: 2012 5th IAPR International Conference on Biometrics (ICB), pp. 390–395. IEEE (2012)
Jain, A., Nandakumar, K., Ross, A.: Score normalization in multimodal biometric systems. Pattern Recogn. 38, 2270–2285 (2005)
Fierrez-Aguilar, J., Ortega-Garcia, J., Garcia-Romero, D., Gonzalez-Rodriguez, J.: A comparative evaluation of fusion strategies for multimodal biometric verification. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, pp. 830–837. Springer, Heidelberg (2003). doi:10.1007/3-540-44887-X_96
Ross, A., Jain, A.: Information fusion in biometrics. Pattern Recogn. Lett. 24, 2115–2125 (2003)
He, M., Horng, S.J., Fan, P., Run, R.S., Chen, R.J., Lai, J.L., Khan, M.K., Sentosa, K.O.: Performance evaluation of score level fusion in multimodal biometric systems. Pattern Recogn. 43, 1789–1800 (2010)
Muramatsu, D., Iwama, H., Makihara, Y., Yagi, Y.: Multi-view multi-modal person authentication from a single walking image sequence. In: 2013 International Conference on Biometrics (ICB), pp. 1–8. IEEE (2013)
Choudhary, A., Chaudhury, S.: Gait recognition based online person identification in a camera network. In: Jawahar, C.V., Shan, S. (eds.) ACCV 2014. LNCS, vol. 9008, pp. 145–156. Springer, Heidelberg (2015). doi:10.1007/978-3-319-16628-5_11
Man, J., Bhanu, B.: Individual recognition using gait energy image. IEEE Trans. Pattern Anal. Mach. Intell. 28, 316–322 (2006)
Iwashita, Y., Sakano, H., Kurazume, R.: Gait recognition robust to speed transition using mutual subspace method. In: Murino, V., Puppo, E. (eds.) ICIAP 2015. LNCS, vol. 9279, pp. 141–149. Springer, Heidelberg (2015). doi:10.1007/978-3-319-23231-7_13
Acknowledgement
This work was supported by JSPS Grants-in-Aid for Scientific Research (A) JP15H01693, the JST CREST “Behavior Understanding based on Intention-Gait Model” project and Nanjing University of Science and Technology.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Hasan, M., Makihara, Y., Muramatsu, D., Yagi, Y. (2017). Gait Gate: An Online Walk-Through Multimodal Biometric Verification System Using a Single RGB-D Sensor. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10118. Springer, Cham. https://doi.org/10.1007/978-3-319-54526-4_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-54526-4_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-54525-7
Online ISBN: 978-3-319-54526-4
eBook Packages: Computer ScienceComputer Science (R0)