Skip to main content
SpringerLink
Log in

Active vision for controlling an electric wheelchair

  • Original Research Paper
  • Published:
Intelligent Service Robotics Aims and scope Submit manuscript

Abstract

Most of the electric wheelchairs available in the market are joystick-driven and therefore assume that the user is able to use his hand motion to steer the wheelchair. This does not apply to many users that are only capable of moving the head like quadriplegia patients. This paper presents a vision-based head motion tracking system to enable such patients of controlling the wheelchair. The novel approach that we suggest is to use active vision rather than passive to achieve head motion tracking. In active vision-based tracking, the camera is placed on the user’s head rather than in front of it. This makes tracking easier, more accurate and enhances the resolution. This is demonstrated theoretically and experimentally. The proposed tracking scheme is then used successfully to control our electric wheelchair to navigate in a real world environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Ashdown M, Oka K, Sato Y (2005) Combining head tracking and mouse input for a GUI on multiple monitors. In: CHI ’05 extended abstracts on human factors in computing systems. ACM, pp 1188–1191

  2. Azarbayejani A, Starner T, Horowitz B, Pentland A (1993) Visually Controlled Graphics. IEEE Trans Pattern Anal Mach Intell 15(6): 602–605

    Article  Google Scholar 

  3. Christensen HV, Garcia JC (2005) Infrared non-contact head sensor, for control of wheelchair movements. In: Pruski A, Knops H (eds) Assistive technology: from virtuality to reality. IOS Press, Amsterdam, pp 336–340

    Google Scholar 

  4. Civera J, Grasa OG, Davison AJ, Montiel JMM (2010) 1-Point RANSAC for extended Kalman filtering: application to real-time structure from motion and visual odometry. J Field Robot 27(5): 609–631

    Article  MATH  Google Scholar 

  5. Fischler M, Bolles R (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24(6): 381–395

    Article  MathSciNet  Google Scholar 

  6. Ford J, Sheredos S (1995) Ultrasonic head controller for powered wheelchairs. J Rehabil Res Dev 32(2): 280–284

    Google Scholar 

  7. Hartley RI, Zisserman A (2004) Multiple view geometry in computer vision, 2nd edn. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  8. Jia P, Hu HH, Lu T, Yuan K (2007) Head gesture recognition for hands-free control of an intelligent wheelchair. Ind Robot 34(1): 60–68

    Article  Google Scholar 

  9. Liu Z, Zhang Z (2000) Robust head motion computation by taking advantage of physical properties. In: Proceedings of the workshop on human motion (HUMO’00), pp 73–77

  10. Lowe D (1999) Object recognition from local scale-invariant features. In: Proceedings of the international conference on computer vision, ICCV ’99

  11. Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2): 91–110

    Article  Google Scholar 

  12. Mandel C, Röfer T, Frese U (2007) Applying a 3d of orientation tracker as a human-robot interface for autonomous wheelchairs. In: Proceedings of the IEEE international conference on rehabilitation robotics

  13. Matsumoto Y, Ino T, Ogasawara T (2001) Development of intelligent wheelchair system with face and gaze based interface. In: Proceedings of 10th IEEE international workshop on robot and human communication, pp 262–267

  14. Mikolajczyk K, Schmid C (2003) A performance evaluation of local descriptors. In: Proceedings of the international conference on computer vision and pattern recognition, vol 2, pp 257–263

  15. Nistér D (2004) An efficient solution to the five-point relative pose problem. IEEE PAMI 26(6): 756–777

    Article  Google Scholar 

  16. Rekimoto J (1995) A vision-based head tracker for fish tank virtual reality—VR without head gear. In: Proceedings of the virtual reality annual international symposium. IEEE Computer Society

  17. Schiele B, Pentland A (1999) Attentional objects for visual context understanding. Tech. Rep. 500, MIT Media Lab

  18. Simpson RC, Levine SP (2002) Voice control of a powered wheelchair. IEEE Trans Neural Syst Rehabil Eng 10(2): 122–125

    Article  Google Scholar 

  19. Sugimoto A, Matsuyama T (2003) Active wearable vision sensor: detecting person’s blink points and estimating human motion trajectory. In: Proceedings of the international conference on advanced intelligent mechatronics, vol 1, pp 539–545

  20. Tordoff B, de Campos WMT, Murray D (2002) Head pose estimation for wearable robot control. In: Proceedings of the 13th British machine vision conference, vol 2, pp 807–816

  21. ur Réhman S (2010) Expressing emotions through vibrations. Ph.D. thesis, Umeå University, Sweden

  22. ur Réhman S, Raytchev B, Yoda I, Liu L (2009) Vibrotactile Rendering of head gestures for controlling electric wheelchair. In: Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics, pp 413–417

  23. Yao Z, Li H (2004) Is a magnetic sensor capable of evaluating a vision-based face tracking system? In: Proceedings of the 2004 conference on computer vision and pattern recognition workshop, Washington, DC, USA

  24. Yoda I, Sakaue K, Inoue T (2007) Development of head gesture interface for electric wheelchair. In: Proceedings of the 1st international convention on Rehabilitation engineering and assistive technology, pp 77–80

Download references

Author information

Authors and Affiliations

  1. Digital Media Lab, Department of Applied Physics and Electronics, Umeå University, 90187, Umeå, Sweden

    Alaa Halawani, Shafiq ur Réhman, Haibo Li & Adi Anani

  2. Department of Electrical and Computer Engineering, Palestine Polytechnic University, Hebron, Palestine

    Alaa Halawani

Authors
  1. Alaa Halawani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shafiq ur Réhman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Haibo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Adi Anani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alaa Halawani.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Halawani, A., ur Réhman, S., Li, H. et al. Active vision for controlling an electric wheelchair. Intel Serv Robotics 5, 89–98 (2012). https://doi.org/10.1007/s11370-011-0098-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11370-011-0098-3

Keywords

Search

Navigation