J. Chung, C. Gulcehre, K. Cho, and Y. Bengio, Empirical evaluation of gated recurrent neural networks on sequence modeling, 2014.

G. Giorgi, Try Walking in My Shoes, if You Can: Accurate Gait Recognition Through Deep Learning, International Conference on Computer Safety, Reliability, and Security, 2017.

Y. Lecun, Y. Bengio, and G. Hinton, Deep learning, nature, vol.521, p.436, 2015.

C. K. Coursey and J. A. Stuller, Linear interpolation lattice, IEEE Transactions on signal processing, vol.39, pp.965-967, 1991.

E. Van-vollenhoven, H. Reuver, and J. Somer, Transient response of Butterworth filters, IEEE Transactions on Circuit Theory, vol.12, pp.624-626, 1965.

A. Buriro, Hold and sign: A novel behavioral biometrics for smartphone user authentication, Security and Privacy Workshops (SPW), 2016.

D. Gafurov, P. Bours, and E. Snekkenes, User authentication based on foot motion, Signal, Image and Video Processing, vol.5, p.457, 2011.

Y. Zhang, Accelerometer-based gait recognition by sparse representation of signature points with clusters, IEEE transactions on cybernetics, vol.45, pp.1864-1875, 2015.

S. Sprager and M. B. Juric, Inertial sensor-based gait recognition: a review, Sensors, vol.15, pp.22089-22127, 2015.

L. Bao and S. S. Intille, Activity recognition from user-annotated acceleration data, International Conference on Pervasive Computing, 2004.

Y. Ren, User verification leveraging gait recognition for smartphone enabled mobile healthcare systems, IEEE Transactions on Mobile Computing, vol.14, pp.1961-1974, 2015.

Z. Wu and G. Pan, Smartshadow: models and methods for pervasive computing, 2013.

D. Muramatsu, Y. Makihara, and Y. Yagi, View transformation model incorporating quality measures for cross-view gait recognition, IEEE transactions on cybernetics, vol.46, pp.1602-1615, 2016.

M. Alotaibi and A. Mahmood, Improved gait recognition based on specialized deep convolutional neural network, Computer Vision and Image Understanding, vol.164, pp.103-110, 2017.

S. Choudhury, T. Das, and . Tjahjadi, Robust view-invariant multiscale gait recognition, Pattern Recognition, vol.48, pp.798-811, 2015.

Q. Zou, Robust gait recognition by integrating inertial and RGBD sensors, IEEE transactions on cybernetics, vol.48, pp.1136-1150, 2018.

Y. Zhang, Accelerometer-based gait recognition by sparse representation of signature points with clusters, IEEE transactions on cybernetics, vol.45, pp.1864-1875, 2015.

F. Martinelli, A. Saracino, and M. Sheikhalishahi, Modeling privacy aware information sharing systems: A formal and general approach, IEEE, 2016.

O. M. Parkhi, A. Vedaldi, and A. Zisserman, Deep Face Recognition, BMVC, vol.1, issue.3, 2015.

A. Krizhevsky, I. Sutskever, and G. E. Hinton, Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, 2012.

A. Graves, A. Mohamed, and G. Hinton, Speech recognition with deep recurrent neural networks, Acoustics, speech and signal processing (icassp), 2013 ieee international conference on, 2013.

K. Cho, Learning phrase representations using RNN encoderdecoder for statistical machine translation, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01433235

D. P. Kingma and J. Ba, Adam: A method for stochastic optimization, 2014.

M. Yang, iGAIT: an interactive accelerometer based gait analysis system, vol.108, pp.715-723, 2012.