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A Fuzzy Ontology-Based System for Gait Recognition Using Kinect Sensor

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Scalable Uncertainty Management (SUM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10564))

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Abstract

Gait recognition involves the automatic classification of human people from sequences of data about their movement patterns. This paper describes our ongoing work in the development of a gait recognition system using Microsoft Kinect data and based on fuzzy ontologies to manage the imprecision of the data and to improve the system scalability.

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References

  1. Bobillo, F., Straccia, U.: Fuzzy ontology representation using OWL 2. Int. J. Approx. Reason. 52(7), 1073–1094 (2011)

    Article  MathSciNet  Google Scholar 

  2. Bobillo, F., Straccia, U.: The fuzzy ontology reasoner fuzzyDL. Knowl.-Based Syst. 95, 12–34 (2016)

    Article  Google Scholar 

  3. Diaz-Rodriguez, N., Pegalajar-Cuellar, M., Lilius, J., Delgado, M.: A fuzzy ontology for semantic modelling and recognition of human behaviour. Knowl.-Based Syst. 66, 46–60 (2014)

    Article  Google Scholar 

  4. Díaz Rodríguez, N., Wikström, R., Lilius, J., Cuéllar, M.P., Delgado Calvo Flores, M.: Understanding movement and interaction: an ontology for kinect-based 3D depth sensors. In: Urzaiz, G., Ochoa, S.F., Bravo, J., Chen, L.L., Oliveira, J. (eds.) UCAmI 2013. LNCS, vol. 8276, pp. 254–261. Springer, Cham (2013). doi:10.1007/978-3-319-03176-7_33

    Chapter  Google Scholar 

  5. Horridge, M., Tudorache, T., Nyulas, C., Vendetti, J., Noy, N.F., Musen, M.A.: WebProtege: a collaborative web-based platform for editing biomedical ontologies. Semant. Web 4(1), 89–99 (2013)

    Google Scholar 

  6. Jiang, S., Wang, Y., Zhang, Y., Sun, J.: Real time gait recognition system based on Kinect skeleton feature. In: Jawahar, C.V., Shan, S. (eds.) ACCV 2014. LNCS, vol. 9008, pp. 46–57. Springer, Cham (2015). doi:10.1007/978-3-319-16628-5_4

    Google Scholar 

  7. Kastaniotis, D., Theodorakopoulos, I., Economou, G., Fotopoulos, S.: Gait based recognition via fusing information from euclidean and riemannian manifolds. Pattern Recogn. Lett. 84, 245–251 (2016)

    Article  Google Scholar 

  8. Kastaniotis, D., Theodorakopoulos, I., Theoharatos, C., Economou, G., Fotopoulos, S.: A framework for gait-based recognition using Kinect. Pattern Recogn. Lett. 68(Part 2), 327–335 (2015)

    Article  Google Scholar 

  9. Preis, J., Kessel, M., Werner, M., Linnhoff-Popien, C.: Gait recognition with Kinect. In: Proceedings of the 1st International Workshop on Kinect in Pervasive Computing, pp. P1–P4 (2012)

    Google Scholar 

  10. Smith, T.C., Frank, E.: Introducing machine learning concepts with WEKA. In: Mathé, E., Davis, S. (eds.) Statistical Genomics. MMB, vol. 1418, pp. 353–378. Springer, New York (2016). doi:10.1007/978-1-4939-3578-9_17

    Chapter  Google Scholar 

  11. Straccia, U.: Foundations of Fuzzy Logic and Semantic Web Languages. CRC Studies in Informatics Series. Chapman & Hall, New York (2013)

    MATH  Google Scholar 

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Acknowledgement

We were funded by DGA/FEDER and projects UZCUD 2016-TEC-02 (University of Zaragoza and Defense University Center), TIN2013-46238-C4 and TIN2016-78011-C4 (Ministerio de Economía y Competitividad).

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Authors and Affiliations

  1. Aragon Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, Spain

    Fernando Bobillo & Jorge Bernad

  2. Defense University Center (CUD), General Military Academy, Zaragoza, Spain

    Lacramioara Dranca

Authors
  1. Fernando Bobillo
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  2. Lacramioara Dranca
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  3. Jorge Bernad
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Corresponding author

Correspondence to Fernando Bobillo .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Serafín Moral

  2. University of Rennes I, Lannion, France

    Olivier Pivert

  3. University of Granada, Granada, Spain

    Daniel Sánchez

  4. University of Granada, Granada, Spain

    Nicolás Marín

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Bobillo, F., Dranca, L., Bernad, J. (2017). A Fuzzy Ontology-Based System for Gait Recognition Using Kinect Sensor. In: Moral, S., Pivert, O., Sánchez, D., Marín, N. (eds) Scalable Uncertainty Management. SUM 2017. Lecture Notes in Computer Science(), vol 10564. Springer, Cham. https://doi.org/10.1007/978-3-319-67582-4_29

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  • DOI: https://doi.org/10.1007/978-3-319-67582-4_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67581-7

  • Online ISBN: 978-3-319-67582-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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