Human Gait Model for Automatic Extraction andDescription for Gait Recognition

Ashish Bhangale1 , Navneet Manjhi2 and Jyoti Bharti3

1Research Scholar, CSE Dept. MANIT-Bhopal, India

2Research Scholar, CSE Dept. MANIT-Bhopal, India

3Asst. Professor, CSE Dept., MANIT-Bhopal, India

ABSTRACT
The gait signature is extracted directly from the evidence gathering process. This is possible by using a Fourier series to describe the motion of the upper leg and apply temporal evidence gathering techniques to extract the moving model from a sequence of images. The improved classification capability of the phase-weighted magnitude information is verified using statistical analysis of the separation of clusters in the feature space. Furthermore, the technique is shown to be able to handle high levels of occlusion, which is of especial importance in gait as the human body is self-occluding. As such, a new technique has been developed to automatically extract and describe a moving articulated shape, the human leg, and shown its potential in gait as a biometric.

KEYWORDS
Fourier series, sequence of images, classification, phase-weighted magnitude, statistical analysis, occulation, articulated shape, biometric, VHT, HVHT, GAVHT, GA, SHT, CCD, FS & HHT