Skip to main content

A New Method of Breakpoint Connection for Human Skeleton Image

  • Chapter
  • First Online:
  • 745 Accesses

Part of the book series: Studies in Computational Intelligence ((SCI,volume 566))

Abstract

There are many discontinuous skeleton points in human skeleton images, which make human skeleton behavior analysis be a difficult problem. Our paper presents a new breakpoint algorithm based on layer and partition of the neighborhood. We scan skeleton images line by line. The number of other skeleton points is calculated for each skeleton point in its 8-neighborhood. Then we judge whether this skeleton point is a breakpoint or not according to the number of the above-obtained and the distribution of other skeleton points in its 8-neighborhood. If it is, we will find available connection skeleton points which can connect the breakpoint. Finally, we find out the points that need to be updated to complete the breakpoint connection progress in accordance with linear equations established by the breakpoint and available connection points. Through of theory analysis and experiment verification, our method has good effect on connecting breakpoints in skeleton images and the shapes of skeleton images are undeformed. In addition to the human skeleton images, this method can also be used for other objects skeleton images on the breakpoints connection.

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 EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   109.99
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

Learn about institutional subscriptions

References

  1. Alvarez-Alvarez, A., Trivino, G., Cord, O.: Body posture recognition by means of a genetic fuzzy finite state machine. In: IEEE 5th International Workshop, Genetic and evolutionary fuzzy systems (GEFS), vol. 4, pp. 60–65 (2011)

    Google Scholar 

  2. Schnell, T., Keller, M., Poolman, P.: A quality of training effectiveness assessment (QTEA): a neurophysiologically based method enhance flight training. Digital Avionics Systems Conference,vol. 10, pp. 4.D.6-1–4.D.6-13 (2008)

    Google Scholar 

  3. Hoinville, T., Naceri, A.: Performances of experienced and novice sportball players in heading virtual spinning soccer balls. In: Virtual Reality Conference (VR) vol. 3, pp. 83–86 (2011)

    Google Scholar 

  4. Ahad, M.A.R., Tan, J., Kim, H., Ishikawa, S.: Action recognition by employing combined directional motion history and energy images. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), vol. 6, pp. 73–78 (2010)

    Google Scholar 

  5. Rosales, R., Sclaroff, S.: Specialized mappings and the estimation of human body pose from a single image. In: Workshop on Human Motion, vol. 3, pp. 19–24 (2000)

    Google Scholar 

  6. Lohou, C., Bertrand, G.: A 3D 6-subiteration curve thinning algorithm based on beta-simple points. Discrete Appl. Math. 151, 1–3 (2005)

    Article  MathSciNet  Google Scholar 

  7. Fei, X., Guili, X., Yuehua, C.: An improved thinning algorithm for human body recognition. In: IEEE International Workshop on Imaging System and Techniques, pp. 411–415 (2009)

    Google Scholar 

  8. Yang, F., Shundong, Z.: Effective mixed fingerprint image thinning algorithm. In: Proceeding of Information Technology and Environmental System Sciences, pp. 116–122 (2008)

    Google Scholar 

  9. Basak, J., Pal, N.R., Patel, P.S.: Thinning in binary and gray images: a connectionist approach. J. Inst. Electron. Telecommun. Eng. 4(42), 305–313 (1996)

    Google Scholar 

  10. Perrot, R.H., Holt, C., Clint, M., Stewart, A.: A parallel processing algorithm for thinning. Digitized Pictures Lect. Notes Comput. Sci. 237, 183–189 (1986)

    Article  Google Scholar 

  11. Hilaire, X., Tombre, K.: Robust and accurate vectorization of line drawings. IEEE Trans. Pattern Anal. Mach. Intell. 28(6), 890–904 (2006)

    Article  Google Scholar 

  12. Lu, T., Tai, C.L., Yang, H., Cai, S.: A novel knowledge-based system for interpreting complex engineering drawings: theory, representation, and implementation. IEEE Trans. Pattern Anal. Mach. Intell. 31(8), 1444–1457 (2009)

    Article  Google Scholar 

  13. Tuia, D., Pacifici, F., Kanevski, M.: Classification of very high spatial resolution imagery using mathematical morphology and support vector machines. IEEE Trans. Geosci. Remote Sens. 47(11), 3866–3879 (2009)

    Article  Google Scholar 

  14. Fernandez, J.A., Gonzalez, J.: Multihierarchical graph search. IEEE Trans. Pattern Anal. Mach. Intell. 24(1), 103–113 (2002)

    Article  Google Scholar 

  15. Zhang, G.Y., Liu, G.Z., Zhu, H., Qiu, B.: Ore image thresholding using bi-neighborhood otsu’s approach. Electron. Lett. 46(25), 1666–1668 (2010)

    Article  Google Scholar 

  16. Lohou, C., Bertrand, G.: 3D 6-subiteration curve thinning algorithm based on beta-simple points. Discrete Appl. Math. 151, 1–3 (2005)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Degui Zhao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Li, X., Zhao, D., Hu, Y., Song, Y., Fu, N., Liu, Q. (2015). A New Method of Breakpoint Connection for Human Skeleton Image. In: Lee, R. (eds) Computer and Information Science. Studies in Computational Intelligence, vol 566. Springer, Cham. https://doi.org/10.1007/978-3-319-10509-3_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-10509-3_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10508-6

  • Online ISBN: 978-3-319-10509-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics