People Identification Using Gait Via Floor Pressure Sensing and Analysis

Authors:
Gang Qian;Jiqing Zhang;Assegid Kidané
Affiliations:
Arts, Media and Engineering Program, and Department of Electrical Engineering, Arizona State University, Tempe, USA AZ 85287;Arts, Media and Engineering Program, and Department of Electrical Engineering, Arizona State University, Tempe, USA AZ 85287;Arts, Media and Engineering Program,
Venue:
EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
Year:
2008

Citing 7
Cited 3

Mean Shift, Mode Seeking, and Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence
The smart floor: a mechanism for natural user identification and tracking

CHI '00 Extended Abstracts on Human Factors in Computing Systems
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
Dynamic footprint-based person recognition method using a hidden markov model and a neural network: Research Articles

International Journal of Intelligent Systems - Intelligent and Soft Computing Techniques for Information Processing
A Floor Sensor System for Gait Recognition

AUTOID '05 Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies
The design of a pressure sensing floor for movement-based human computer interaction

EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
User identification using user’s walking pattern over the ubiFloorII

CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I

Hallway monitoring: distributed data processing with wireless sensor networks

REALWSN'10 Proceedings of the 4th international conference on Real-world wireless sensor networks
GravitySpace: tracking users and their poses in a smart room using a pressure-sensing floor

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
On optimal operator for combining left and right sole pressure data in biometrics security

Advances in Fuzzy Systems

Quantified Score

Hi-index	0.01

Visualization

Abstract

This paper presents an approach to people identification using gait based on floor pressure data. By using a large area high resolution pressure sensing floor, we were able to obtain 3D trajectories of the center of foot pressures over a footstep which contain both the 1D pressure profile and 2D position trajectories of the COP. Based on the 3D COP trajectories a set of features are then extracted and used for people identification together with other features such as stride length and cadence. The Fisher linear discriminant is used as the classifier. Encouraging results have been obtained using the proposed method with an average recognition rate of 94% and false alarm rate of 3% using pair-wise footstep data from 10 subjects.