Gait Recognition by Fitting Moment Invariants
不变矩系数拟合的步态识别

According to the idea of combining static components and dynamic components from the walking way, as the moment invariants may represent geometrical traits in images, they were extracted as gait features from a subsequent gait series. The moment invariants of human silhouettes were represented by the Fourier series. A genetic algorithm was deployed to obtain the Fourier coefficients. The magnitudes of the coefficients were classified through the kNN classifier. The recognition restdts with the proposed scheme in the CMU gait database have recognition rates of more than 90% and show that it has achieved a high performance and effectively made use of two kinds of contents.