Skip to main content

Combining Pattern Matching and Optical Flow Methods in Home Care Vision System

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 7339))

Abstract

The article presents the structure and working of the system supervising the convalescent or elder person at home. Images acquired from a suitably mounted camera are analyzed to determine the pose and activity of the observed person. Extensive configuration module allows to define zones of rest and obstructing objects. Situations of long immobility are detected in places where it should not happen. The activity of observed person is computed using two independent methods: by counting the number of frames in which the active poses are detected and by counting the number of frames, in which the dominant component of the optical flow histogram exceeded the threshold value. By keeping methods of image analysis as simple as possible the processing time was achieved close to the real-time.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Buccolieri, F., Distante, C., Leone, A.: Human posture recognition using active contours and radial basis function neural network. IEEE Advanced Video and Signal Based Surveillance, 213–218 (2005), doi:10.1109/AVSS.2005.1577269

    Google Scholar 

  2. Chen S., Folowosele F., Kim D., Vogelstein R.J., Etienne-Cummings, R., Culurciello, E.: A size and position invariant event-based human posture recognition algorithm. IEEE Biomedical Circuits and Systems Conference, doi: 10.1109/BIOCAS.2008.4696930, pp. 285–288 (2008).

    Google Scholar 

  3. Fleet, D.J., Weiss, Y.: Mathematical Models in Computer Vision. The Handbook, Optical Flow Estimation, ch. 15, pp. 239–258. Springer (2005)

    Google Scholar 

  4. Goldman, L., Karaman, M., Sikora, T.: Human body posture recognition using MPEG-7 descriptors. In: Proc. SPIE 5308, vol. 177 (2004), doi:10.1117/12.526666

    Google Scholar 

  5. Martinez J. M.: MPEG-7 Overview (2004), http://www.chiariglione.org/mpeg/standards/mpeg-7/mpeg-7.htm

  6. Mikrut, Z., Smoleń, M.: A neural network approach to recognition of the selected human motion patterns. Automatyka 15(3), 535–543 (2011)

    Google Scholar 

  7. Rowe, D.: Towards robust multiple-target tracking in unconstrained human-populated environments. In: Reviewing Detections and Tracking Approaches, ch. 2, Universitat Autonoma de Barcelona, Spain (2008)

    Google Scholar 

  8. Tadeusiewicz, R.: Place and role of intelligent systems in computer science. Computer Methods in Materials Science 10(4), 193–206 (2010)

    Google Scholar 

  9. Vezzani, R., Baltieri, D., Cucchiara, R.: HMM Based Action Recognition with Projection Histogram Features. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds.) ICPR 2010. LNCS, vol. 6388, pp. 286–293. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  10. Opera Unite, http://unite.opera.com/overview

  11. OpenCV, http://opencv.willowgarage.com

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mikrut, Z., Pleciak, P., Smoleń, M. (2012). Combining Pattern Matching and Optical Flow Methods in Home Care Vision System. In: Piętka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Lecture Notes in Computer Science(), vol 7339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31196-3_54

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-31196-3_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31195-6

  • Online ISBN: 978-3-642-31196-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics