Gait Recognition using Sampled Point Vectors

Gait is a new biometric aimed to recognize individuals by the way they walk. Gait recognition has recently an increasing interest from researchers due to several advantages. In this paper, we have proposed a new feature vector, sampled point vector, for gait recognition based on model-free method. We choose the mean and variance of value of pixels which are sampled along to central axis of silhouette image for several frames. In contract to other system, proposed features are very simple and require low storages. Nevertheless, experimental result show sufficiently good performance. To evaluate, we use a reduced multivariate model as a classifier