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Gait Recognition Using Normalized Shadows

Verlekar, TTV ; Correia, P.L. ; Soares, L. D.

Gait Recognition Using Normalized Shadows, Proc European Signal Processing Conference EUSIPCO, kos, Greece, Vol. , pp. - , August, 2017.

Digital Object Identifier: 10.23919/EUSIPCO.2017.8081345

Abstract
Surveillance of public spaces is often conducted
with the help of cameras placed at elevated positions. Recently,
drones with high resolution cameras have made it possible to
perform overhead surveillance of critical spaces. However,
images obtained in these conditions may not contain enough body
features to allow conventional biometric recognition. This paper
introduces a novel gait recognition system which uses the
shadows cast by users, when available. It includes two main
contributions: (i) a method for shadow segmentation, which
analyzes the orientation of the silhouette contour to identify the
feet position along time, in order to separate the body and
shadow silhouettes connected at such positions; (ii) a method that
normalizes the segmented shadow silhouettes, by applying a
transformation derived from optimizing the low rank textures of
a gait texture image, to compensate for changes in view and
shadow orientation. The normalized shadow silhouettes can then
undergo a gait recognition algorithm, which in this paper relies
on the computation of a gait energy image, combined with linear
discriminant analysis for user recognition. The proposed system
outperforms the available state-of-the-art, being robust to
changes in acquisition viewpoints.