  Gait and static body measurement are important biometric technologies for
passive human recognition. Many previous works argue that recognition
performance based completely on the gait feature is limited. The reason for
this limited performance remains unclear. This study focuses on human
recognition with gait feature obtained by Kinect and shows that gait feature
can effectively distinguish from different human beings through a novel
representation -- relative distance-based gait features. Experimental results
show that the recognition accuracy with relative distance features reaches up
to 85%, which is comparable with that of anthropometric features. The
combination of relative distance features and anthropometric features can
provide an accuracy of more than 95%. Results indicate that the relative
distance feature is quite effective and worthy of further study in more general
scenarios (e.g., without Kinect).
