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Journal cover: Industrial Robot: An International Journal

Industrial Robot: An International Journal

ISSN: 0143-991X

Online from: 1973

Subject Area: Mechanical & Materials Engineering

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Head gesture recognition for hands-free control of an intelligent wheelchair


Document Information:
Title:Head gesture recognition for hands-free control of an intelligent wheelchair
Author(s):Pei Jia, (Department of Computer Science, University of Essex, Colchester, UK), Huosheng H. Hu, (Department of Computer Science, University of Essex, Colchester, UK), Tao Lu, (Institute of Automation, Chinese Academy of Sciences, Beijing, People's Republic of China), Kui Yuan, (Institute of Automation, Chinese Academy of Sciences, Beijing, People's Republic of China)
Citation:Pei Jia, Huosheng H. Hu, Tao Lu, Kui Yuan, (2007) "Head gesture recognition for hands-free control of an intelligent wheelchair", Industrial Robot: An International Journal, Vol. 34 Iss: 1, pp.60 - 68
Keywords:Automation, Wheelchairs
Article type:Research paper
DOI:10.1108/01439910710718469 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Abstract:

Purpose – This paper presents a novel hands-free control system for intelligent wheelchairs (IWs) based on visual recognition of head gestures.

Design/methodology/approach – A robust head gesture-based interface (HGI), is designed for head gesture recognition of the RoboChair user. The recognised gestures are used to generate motion control commands to the low-level DSP motion controller so that it can control the motion of the RoboChair according to the user's intention. Adaboost face detection algorithm and Camshift object tracking algorithm are combined in our system to achieve accurate face detection, tracking and gesture recognition in real time. It is intended to be used as a human-friendly interface for elderly and disabled people to operate our intelligent wheelchair using their head gestures rather than their hands.

Findings – This is an extremely useful system for the users who have restricted limb movements caused by some diseases such as Parkinson's disease and quadriplegics.

Practical implications – In this paper, a novel integrated approach to real-time face detection, tracking and gesture recognition is proposed, namely HGI.

Originality/value – It is an useful human-robot interface for IWs.



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