Classification of age groups using walking data obtained from a Laser Range Scanner

Shiori Sakai, Sumire Kimura, Daiki Nomiyama, Takamasa Ikeda, Nobuto Matsuhira, Yuka Kato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We have studied a dialog control method for interface robots by using location data of persons measured by a Laser Range Scanner as a human-robot interaction technology. In the method, we measured the distance between a sensor and a person with the sensor placed at human waist height as a time series data and estimated the position coordinates of the person at a time as a probability distribution. This paper extends the scheme and proposes a method estimating person attributes in addition to the location data by monitoring the movement of legs while the person is walking. As for person attributes, we focus on the age and classify persons as the elderly and the young. At that time, we construct a prediction model of age groups based on machine learning mechanisms. In this paper, we use seven feature values, these are the step length, the step width, the velocity of leg 1, the velocity of leg 2, the velocity of body, the acceleration of leg 1 and the acceleration of leg 2 for the model. By conducting experiments, we verify that classification accuracy improves particularly using acceleration and standard deviation of the data.

Original languageEnglish
Title of host publicationProceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society
PublisherIEEE Computer Society
Pages5862-5867
Number of pages6
ISBN (Electronic)9781509034741
DOIs
Publication statusPublished - 2016 Dec 21
Event42nd Conference of the Industrial Electronics Society, IECON 2016 - Florence, Italy
Duration: 2016 Oct 242016 Oct 27

Publication series

NameIECON Proceedings (Industrial Electronics Conference)

Other

Other42nd Conference of the Industrial Electronics Society, IECON 2016
CountryItaly
CityFlorence
Period16/10/2416/10/27

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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