We propose a method of gait identification based on multi-view gait images using an omnidirectional camera. We first transform omnidirectional silhouette images into panoramic ones and obtain a spatio-temporal Gait Silhouette Volume (GSV). Next, we extract frequency- domain 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, multi-view 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.
Gait Identification Based on Multi-view Observations Using Omnidirectional Camera
Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007
2007-01-01
10 pages
Article/Chapter (Book)
Electronic Resource
English
False Alarm Rate , Azimuth Angle , Gait Feature , Gait Recognition , Omnidirectional Image Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence , Biometrics , Algorithm Analysis and Problem Complexity
Multi-lane detection based on omnidirectional camera using anisotropic steerable filters
IET | 2016
|The Gait of an Omnidirectional Walking Vehicle
British Library Conference Proceedings | 1993
|Normalization-Based Omnidirectional Gait Planning for Small Humanoid Robot
Trans Tech Publications | 2011
|