Detection of multiple people by a mobile robot in dynamic indoor environments

  • Authors:

  • José Alberto Méndez-Polanco;Angélica Muñoz-Meléndez;Eduardo F. Morales-Manzanares

  • Affiliations:

  • National Institute of Astrophysics, Optics and Electronics, Computer Science Department, Tonantzintla, México;National Institute of Astrophysics, Optics and Electronics, Computer Science Department, Tonantzintla, México;National Institute of Astrophysics, Optics and Electronics, Computer Science Department, Tonantzintla, México

  • Venue:
  • IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

Detection of multiple people is a key element for social robot design and it is a requirement for effective human-robot interaction. However, it is not an easy task, especially in complex real world scenarios that commonly involve unpredictable motion of people. This paper focuses on detecting multiple people with a mobile robot by fusing information from different sensors over time. The proposed approach applies a segmentation method that uses the distance to the objects to separate possible people from the background and a novel adaptive contour people model to obtain a probability of detecting people. A probabilistic skin model is also applied to the images and both evidences are merged and used over time with a Bayesian scheme to detect people. We present experimental results that demonstrate how the proposed method is able to detect people who is standing, sitting and leaning sideways using a mobile robot in cluttered real world scenarios.