View-Invariant and Robust Gait Recognition Using Gait Energy Images of Leg Region and Masking Altered Sections

There are two serious issues regarding gait recognition. The first issue presents when the walking direction is unknown and the other one presents when the appearance of the user changes due to various reasons including carrying a bag or changing clothes. In this paper, a two-step view-invariant robust system is proposed to address these. In the first step, the walking direction is determined using five features of pixels of the leg region from gait energy image (GEI). In the second step, the GEI is decomposed into rectangular sections and the influence of changes in the appearance is confined to a small number of sections that could be eliminated by masking these sections. The system performs very well because the first step is computationally inexpensive and the second step preserves more useful information compared to other methods. In comparison with other methods, the proposed method shows better results.