WALKING DIRECTION IDENTIFICATION USING PERCEPTUAL HASHING

Gait has become a popular trait for biometric recognition especially in surveillance environments due to its advantage of being captured without active user participation. However the gait description obtained in such scenarios depends on the observed walking direction of the user. Hence, if the user's walking direction is unknown, comparison against a previously prepared database can be rendered impossible. This paper discusses the problem of identifying the walking direction in an unconstrained environment and proposes a novel approach to identify the walking direction. The walking direction is identified by computing a perceptual hash (PHash) over the leg region of the user and comparing it against the PHash values obtained for training sequences. The proposed method is computationally inexpensive and performs better than the state-of-the-art methods. It is also robust against appearance changes that may be caused for instance by the user wearing a coat or carrying a bag.