  This paper proposes a reliable approach for human gait symmetry assessment
using a depth camera and two mirrors. The input of our system is a sequence of
3D point clouds which are formed from a setup including a Time-of-Flight (ToF)
depth camera and two mirrors. A cylindrical histogram is estimated for
describing the posture in each point cloud. The sequence of such histograms is
then separated into two sequences of sub-histograms representing two
half-bodies. A cross-correlation technique is finally applied to provide values
describing gait symmetry indices. The evaluation was performed on 9 different
gait types to demonstrate the ability of our approach in assessing gait
symmetry. A comparison between our system and related methods, that employ
different input data types, is also provided.
