<abstract xmlns="http://www.w3.org/1999/xhtml"><p>We propose a novel framework to recognize individuals from gait, in order to improve HRI. We collected the motion data of the torso from 13 persons’ gait, using 2 IMU sensors. We developed Feature Value Method which is a PCA based classifier and we achieved an average individual recognition rate of 94% through cross-validation.</p></abstract>

We propose a novel framework to recognize individuals from gait, in order to improve HRI. We collected the motion data of the torso from 13 persons’ gait, using 2 IMU sensors. We developed Feature Value Method which is a PCA based classifier and we achieved an average individual recognition rate of 94% through cross-validation.

Individual Recognition from Gait Using Feature Value Method

Department of Mechanical Systems Engineering, Tokyo Univ. of Agriculture and Technology

Cybernetics and Information Technologies

{"article-title":"Individual Recognition from Gait Using Feature Value Method"}

We propose a novel framework to recognize individuals from gait, in order to improve HRI. We collected the motion data of the torso from 13 persons’ gait,...

Individual Recognition from Gait Using Feature Value Method

Publié en ligne: 22 mars 2013

Pages: 86 - 95

DOI: https://doi.org/10.2478/cait-2012-0024

Mots clés
Gait, Recognition, PCA, Feature vector, Exclusion method

This content is open access.

Individual Recognition from Gait Using Feature Value Method

Publié en ligne: 22 mars 2013

Pages: 86 - 95

DOI: https://doi.org/10.2478/cait-2012-0024

Mots clésGait, Recognition, PCA, Feature vector, Exclusion method

This content is open access.

Mots clés
Gait, Recognition, PCA, Feature vector, Exclusion method