Skip to main content
SpringerLink
Log in

Vision-Based Human Following Method for a Mobile Robot Using Human and Face Detection

  • Conference paper
  • First Online:
Information Technology Convergence

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 253))

  • 785 Accesses

Abstract

This paper presents a method of vision based human following for a mobile robot to trace a given human in an indoor environment. For a mobile robot to perform vision based human tracing reliably, we combined a silhouette based human detection and two-stage face detection technique. In this paper, the human detection uses a Histogram of Oriented Gradient (HOG). The face detection is composed of two stages, face detection using a Haar-like wavelet feature and AdaBoost and face detection using skin color with motion information and validation of contour shape. Finally, the performance of the proposed system is verified by conducting experiments where a mobile robot follows a human successfully in a real indoor environment.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Schlegel C, Illmann J, Jaberg H, Schuster M (1998) Vision based person tracking with a mobile robot. In: Ninth British machine vision conference, BMVC ‘98, Southhampton, pp 418–427

    Google Scholar 

  2. Viola Paul A, Jones Michael J (2001) Robust real-time face detection. ICCV 2:747

    Google Scholar 

  3. Senior A (2002) Tracking people with probabilistic appearance models, IEEE. In: International workshop on performance evaluation of tracking and surveillance, pp 48–55

    Google Scholar 

  4. Papageorgiou C, Oren M, Poggio T (1998) A general framework for object detecion. In: International conference on computer vision, pp 555–562

    Google Scholar 

  5. Barron JI, Fleet DJ, Beauchemin SS (1992) Performance of optical flow techniques, IEEE. In: conference on computer Vision and pattern recognition, pp 236–242

    Google Scholar 

  6. Dalal N, Triggs B, (2005) Histograms of oriented gradients for human detection, IEEE. In: CVPR, vol 1, pp 886–893

    Google Scholar 

  7. Laptev I (2006) Improvements of object detection using boosted histograms, In: Proceeding of British machine vision conference, Edinburgh, UK

    Google Scholar 

  8. Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features, In: proceeding of IEEE. CVPR, Kauai, Hawaii, pp 12–14

    Google Scholar 

  9. Jang Heejun, Ko Hyesun, Choi Youngwoo, Han Youngjoon, Hahn Hernsoo (2005) A new face tracking method using block difference image and kalman filter in moving picture. J Fuzzy Log Intell Syst 15(2):163–172

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (MEST) (2011-0013776).

Author information

Authors and Affiliations

  1. Department of Intelligent Robot Engineering, Mokwon University, Mokwon Gil 21, Seo-gu, Daejeon, Republic of Korea

    Se-Jun Park, Tae-Kyu Yang & Yong-Ho Seo

Authors
  1. Se-Jun Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tae-Kyu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yong-Ho Seo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yong-Ho Seo .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Dept. Information & Communication Engineering, Fukuoka Institute of Technology Fac. Information Engineering, Fukuoka, Japan

    Leonard Barolli

  3. Departament De Llenguatges I Sistemes Informàtics, Universitat Politècnica De Catalunya, Barcelona, Spain

    Fatos Xhafa

  4. Humanitas College, Kyung Hee University, Seoul, Korea, Republic of (South Korea)

    Hwa-Young Jeong

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media Dordrecht

About this paper

Cite this paper

Park, SJ., Yang, TK., Seo, YH. (2013). Vision-Based Human Following Method for a Mobile Robot Using Human and Face Detection. In: Park, J., Barolli, L., Xhafa, F., Jeong, HY. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_94

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-6996-0_94

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6995-3

  • Online ISBN: 978-94-007-6996-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation