Skip to main content
SpringerLink
Log in

Face Detection Based Automation of Electrical Appliances

  • Conference paper
  • First Online:
Computational Vision and Bio-Inspired Computing ( ICCVBIC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1108))

  • 1854 Accesses

Abstract

This paper addresses the problem of automation of electrical appliances with the use of sensors. The proposed method uses Viola-Jones method a real time face detection algorithm for controlling the electrical appliances which are part of our day to day life. A detector is initialized by Viola-Jones based face detection algorithm automatically without the need for any manual intervention. After initializing the detector, the position where the face detected is computed. The region captured by the camera is split into four different regions. Based on the position of the detected face the electrical appliances subjected to that particular region can be controlled.

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Claesson, I.: Face detection using local SMQT features and split up snow classifier. In: 2007 IEEE International Conference on Acoustics Speech and Signal Processing - ICASSP 2007 (2007)

    Google Scholar 

  2. Rowley, H.A., Baluja, S., Kanade, T.: Neural networks based face detection. IEEE Trans. Pattern Anal. Mach. Intell. 20(1), 22–38 (1998)

    Article  Google Scholar 

  3. Sung, K.K., Poggio, T.: Example-based learning for view-based human face detection. IEEE Trans. Pattern Anal. Mach. Intell. 20(1), 39–51 (1998)

    Article  Google Scholar 

  4. Boser, B., Guyon, I.M., Vapnik, V.: A training algorithm for optimal margin classifiers. In: ACM Workshop on Conference on Computational Learning Theory (COLT), pp. 142–152 (1992)

    Google Scholar 

  5. Yilmaz, A., Javed, O., Shah, M.: Object tracking: a survey. ACM Comput. Surv. 38(4), 45 (2006)

    Article  Google Scholar 

  6. Paul, V., Jones, M.J.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 511–518 (2001)

    Google Scholar 

  7. Allen, J.G., Xu, R.Y.D., Jin, J.S.: Object tracking using CamShift algorithm and multiple quantized feature spaces. In: Proceedings of the Pan-Sydney Area Workshop on Visual Information Processing. In: ACM International Conference Proceeding Series, vol. 100, pp. 3–7. Australian Computer Society, Inc., Darlinghurst (2004)

    Google Scholar 

  8. Jain, V., Patel, D.: A GPU based implementation of robust face detection system. Procedia Comput. Sci. 87, 156–163 (2016)

    Article  Google Scholar 

  9. Chatrath, J., Gupta, P., Ahuja, P., Goel, A., Arora, S.M.: Real time human face detection and tracking. In: International Conference on Signal Processing and Integrated Networks (SPIN), pp. 705–710 (2014)

    Google Scholar 

  10. Tao, Q.-Q., Zhan, S., Li, X.-H., Kurihara, T.: Robust face detection using local CNN and SVM based on kernel combination. Neurocomputing 211, 98–105 (2016)

    Article  Google Scholar 

  11. Da’san, M., Alqudah, A., Debeir, O.: Face detection using Viola and Jones method and neural networks. In: International Conference on Information and Communication Technology Research, pp. 40–43 (2015)

    Google Scholar 

  12. Singh, P., Chotalia, K., Pingale, S., Kadam, S.: Smart GSM based home automation system. Int. Res. J. Eng. Technol. (IRJET) 03(04), 19838–19843 (2016)

    Google Scholar 

  13. D’mello, A., Deshmukh, G., Murudkar, M., Tripathi, G.: Home automation using Raspberry Pi 2. Int. J. Curr. Eng. Technol. 6(3), 750–754 (2016)

    Google Scholar 

  14. Kang, S., Choi, B., Jo, D.: Faces detection method based on skin color modeling. J. Syst. Archit. 64, 100–109 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electronics Engineering, Vellore Institute of Technology, Vellore, India

    S. V. Lokesh & B. Karthikeyan

  2. Electronics and Instrumentation Engineering, NIT Nagaland, Dimapur, India

    R. Kumar

  3. Electronics and Communication Engineering, Sri Indu Institute of Engineering and Technology Sheriguda, Hyderabad, India

    S. Suresh

Authors
  1. S. V. Lokesh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. Karthikeyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R. Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S. Suresh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. V. Lokesh .

Editor information

Editors and Affiliations

  1. Department of CSE, RVS Technical Campus, Coimbatore, India

    S. Smys

  2. Faculty of Engineering, Faculdade de Engenharia da Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  3. Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  4. School of Computing, Tokyo Institute of Technology, Tokyo, Japan

    Abdullah M. Iliyasu

Ethics declarations

✓ All authors declare that there is no conflict of interest

✓ No humans/animals involved in this research work.

✓ We have used our own data.

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Lokesh, S.V., Karthikeyan, B., Kumar, R., Suresh, S. (2020). Face Detection Based Automation of Electrical Appliances. In: Smys, S., Tavares, J., Balas, V., Iliyasu, A. (eds) Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing, vol 1108. Springer, Cham. https://doi.org/10.1007/978-3-030-37218-7_23

Download citation

Publish with us

Policies and ethics

Search

Navigation