Ton portable sait te reconnaître au rythme de tes pas. ▻http://users.ece.cmu.edu/~juefeix/btas_2012_felix.pdf
(Il saura également te signaler aux autorités.)
In this paper, we have proposed a robust, acceleration
based, pace independent gait recognition framework us-
ing Android smartphones. From our extensive experiments
using cyclostationarity and continuous wavelet transform
spectrogram analysis on our gait acceleration database
with both normal and fast paced data, our proposed algo-
rithm has outperformed the state-of-the-art by a great mar-
gin. To be more specific, for normal to normal pace match-
ing, we are able to achieve 99.4% verification rate (VR) at
0.1% false accept rate (FAR); for fast vs. fast, we are able to
achieve 96.8% VR at 0.1% FAR; for the challenging normal
vs. fast, we are still able to achieve 61.1% VR at 0.1% FAR.
The findings have laid the foundation of pace independent
gait recognition using mobile devices with high accuracy.