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Analysis of Gait Features between Loaded and Normal Gait

Ever since the beginning of research on gait recognition, the main focus has been on investigating gait as a biometric. For security surveillance systems, the detection of suspicious behavior is considered to be more relevant than the recognition of identity, which applies more to security authentication systems. Hence, this research uses gait features as cues to detect suspicious behavior. In this work, the effect of load bearing on gait is investigated by analyzing the kinematics parameters between normal and loaded gaits to find out the ground truth between them. The focus is on two features computed throughout a video sequence: silhouette attributes attraction and limbs angular displacements attraction. The silhouette attributes use the area and center of mass of objects. The volunteers were carrying 5kg, 10kg, 15kg and 20kg weights in a bag pack attached either to the back or to the front of their bodies. The results show that silhouette area can be a useful descriptor for discriminating between loaded and normal gait. The second feature (limbs angular displacements attraction) also gives a positive result (92.2%) for both loads starting from 10kg attached at the back and front of subjects.