Gait Identification Based on Multi-view Observations Using Omnidirectional Camera

We propose a method of gait identification based on multiview gait images using an omnidirectional camera. We first transform omnidirectional silhouette images intopanoramic ones and obtain a spatiotemporal Gait Silhouette Volume (GSV). Next, we extract frequencydomain features by Fourier analysis based on gait periods estimated by autocorrelation of the GSVs. Because the omnidirectional camera makes it possible to observe a straight-walking person from various views, multiview features can be extracted from the GSVs composed of multi-view images. In an identification phase, distance between a probe and a gallery feature of the same view is calculated, and then these for all views are integrated for matching. Experiments of gait identification including 15 subjects from 5 views demonstrate the effectiveness of the proposed method.