Dynamic footprint-based person recognition method using a hidden Markov model and a neural network

Jin Woo Jung, Tomomasa Sato, Zeungnam Bien

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Many diverse methods have been developed in the field of biometric identification as a greater emphasis is placed on human friendliness in the area of intelligent systems. One emerging method is the use of footprint shape. However, in previous research, there were some limitations resulting from the spatial resolution of sensors. One possible method to overcome this limitation is through the use of additional and independent information such as gait information during walking. In this study, we suggest a new person-recognition scheme based on the center of pressure (COP) trajectory in the dynamic footprint. To make an efficient and automated footprint-based person recognition method using the COP trajectory, we use a hidden Markov model and a neural network. Finally, we demonstrate the usefulness of the suggested method, obtaining an approximately 80% recognition rate using only the COP trajectory in our experiment with 11 people.

Original languageEnglish
Pages (from-to)1127-1141
Number of pages15
JournalInternational Journal of Intelligent Systems
Volume19
Issue number11
DOIs
StatePublished - Nov 2004

Fingerprint

Dive into the research topics of 'Dynamic footprint-based person recognition method using a hidden Markov model and a neural network'. Together they form a unique fingerprint.

Cite this