Robust Gait identification with belongings from back view

Gait is one of the biological information which indicates how to walk. Gait is able to acquire from a distance and any views. It is, however, difficult to identify a person with belongings. The purpose of this paper is, therefore, to propose an effective identification method when the subject has a bag. First, GEI(Gait Energy Image) is generated with head position adjustment. Then, gradient of GEI for head, both arms and leg regions are obtained. Finally, features are obtained from each region except for the hand region with a bag and the bag itself in the leg region. The proposed method obtains 95.0% identification ratio for back view gait with belongings.