Gait recognition using dynamic affine invariants
We present a method for recognizing classes of human gaits from video sequences. We propose a novel image based representation for human gaits. At any instance of time a gait is represented by a vector of affine invariant moments. The invariants are computed on the binary silhouettes corresponding to the moving body. We represent the time trajectories of the affine moment invariant vector as the output of a linear dynamical system driven by white noise. The problem of gait classification is then reduced to formulating distances and performing recognition in the space of linear dynamical systems. Results demonstrating the discriminate power of the proposed methods are discussed at the end.