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Evaluation of Similarity Measuring Method of Human Body Movement Based on 3D Chain Code

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Intelligent Information and Database Systems (ACIIDS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10752))

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Abstract

This paper experimentally evaluates the method for measuring human body movement similarity considering the human body motion as a set of 3-dimensional curves representing the changes of direction. After the direction sequences describing the motion paths are derived, an improved method inspired by the dissimilarity measure of the 3D curves is used for measuring the similarity of human body movements. The tests for statistical significance is used in order to evaluate the efficiency of measure in the experiments. The experimental results show that the proposed method successfully measures the similarity of human body movements for the low complexity dataset and the similar motion types.

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References

  1. Bribiesca, E.: A chain code for representing 3D curves. Pattern Recogn. 33(5), 755–765 (2000)

    Article  MathSciNet  Google Scholar 

  2. Bribiesca, E., Aguilar, W.: A measure of shape dissimilarity for 3D curves. Int. J. Contemp. Math. Sci. 1(15), 727–751 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  3. Davis, R.B., Davids, J.R., Gorton, G.E., Aiona, M., Scarborough, N., Oeffinger, D., Tylkowski, C., Bagley, A.: A minimum standardized gait analysis protocol: development and implementation by the Shriners Motion Analysis Laboratory network (SMALnet). In: Pediatric Gait: A New Millennium in Clinical Care and Motion Analysis Technology, pp. 1–7 (2000)

    Google Scholar 

  4. Freeman, H.: On the encoding of arbitrary geometric configurations. IRE Trans. Electron. Comput. EC-10(2), 260–268 (1961)

    Article  MathSciNet  Google Scholar 

  5. Freeman, H.: Computer processing of line-drawing images. ACM Comput. Surv. (CSUR) 6(1), 57–97 (1974)

    Article  MATH  Google Scholar 

  6. Hochin, T., Nomiya, H.: Deriving pauses for obtaining fundamental movements in traditional skills. In: Lee, R.Y. (ed.) Applied Computing and Information Technology. SCI, vol. 553, pp. 19–30. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-05717-0_2

    Chapter  Google Scholar 

  7. Kume, M., Yoshida, T.: Characteristics of technique or skill in traditional craft workers in Japan. In: Advances in Affective and Pleasurable Design, p. 140 (2012)

    Google Scholar 

  8. Kwon, D.Y.: A study on taekwondo training system using hybrid sensing technique. J. Korea Multimed. Soc. 16(12), 1439–1445 (2013)

    Article  Google Scholar 

  9. Laban, R., Ullmann, L.: Choreutics. Macdonald & Evans, London (1966)

    Google Scholar 

  10. Lin, D.: An information-theoretic definition of similarity. In: Proceedings of the Fifteenth International Conference on Machine Learning, pp. 296–304. Morgan Kaufmann Publishers Inc., Burlington (1998)

    Google Scholar 

  11. Mandery, C., Terlemez, Ö., Do, M., Vahrenkamp, N., Asfour, T.: The KIT whole-body human motion database. In: Proceedings of the International Conference on Advanced Robotics (ICAR), pp. 329–336. IEEE (2015)

    Google Scholar 

  12. Ngan, P.T.H., Hochin, T., Nomiya, H.: Similarity measure of human body movement through 3D chaincode. In: Proceedings of 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), pp. 607–614 (2017)

    Google Scholar 

  13. Okada, Y., Etou, H., Niijima, K.: Intuitive interfaces for motion generation and search. In: Grieser, G., Tanaka, Y. (eds.) Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets. LNCS (LNAI), vol. 3359, pp. 49–67. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-32279-5_4

    Chapter  Google Scholar 

  14. Reyes, F.J.T.: Human motion: analysis of similarity and dissimilarity using orthogonal changes of direction on given trajectories. Dissertation, Department of Computer Science, University of Colorado Colorado Springs (2014)

    Google Scholar 

  15. Schmidt, J., Berg, D.R., Ploeg, H.-L., Ploeg, L.: Precision, repeatability and accuracy of Optotrak® optical motion tracking systems. Int. J. Exp. Comput. Biomech. 1(1), 114–127 (2009)

    Article  Google Scholar 

  16. Shull, P.B., Jirattigalachote, W., Hunt, M.A., Cutkosky, M.R., Delp, S.L.: Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention. Gait Posture 40(1), 11–19 (2014)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Graduate School of Science and Technology, Kyoto Institute of Technology, Kyoto, Japan

    Truong Hong Ngan Pham

  2. Kyoto Institute of Technology, Kyoto, Japan

    Teruhisa Hochin & Hiroki Nomiya

Authors
  1. Truong Hong Ngan Pham
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  2. Teruhisa Hochin
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  3. Hiroki Nomiya
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Corresponding author

Correspondence to Truong Hong Ngan Pham .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Quang Binh University, Dong Hoi City, Vietnam

    Duong Hung Hoang

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Rutgers University, Piscataway, New Jersey, USA

    Hoang Pham

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Pham, T.H.N., Hochin, T., Nomiya, H. (2018). Evaluation of Similarity Measuring Method of Human Body Movement Based on 3D Chain Code. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10752. Springer, Cham. https://doi.org/10.1007/978-3-319-75420-8_44

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  • DOI: https://doi.org/10.1007/978-3-319-75420-8_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75419-2

  • Online ISBN: 978-3-319-75420-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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