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Recognition and Modeling of Atypical Children Behavior

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Artificial Intelligence and Soft Computing (ICAISC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9119))

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Abstract

According to reports from medical community the number of autistic children’s birth is more and more alarming. Early diagnosis and regular rehabilitation are crucial. The problem with verbal and emotional communication is very common. In a form of short survey, a few similar issues and their solutions have been examined in terms of input data type, feature selection, pattern recognition and formal mathematical modeling. Then we propose a system for autistic children rehabilitation, surveillance and emotions translation. These new solutions have been compared with those reported in the literature. The preliminary experiments provide rather satisfactory results.

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References

  1. Ricks, D., Wing, L.: Language, Communication, and the Use of Symbols in Normal and Autistic Children. Journal of Autism and Childhood Schizophrenia 5, 191–221 (1975)

    Article  Google Scholar 

  2. Landowska, A., Kołakowska, A., Anzulewicz, A., Jarmołkowicz, P., Rewera, J.: E-technologies in diagnosis and progress measurement in autistic children therapy in Poland (in Polish). E-mentor 4 (2014)

    Google Scholar 

  3. Snoek, J., Hoey, J., Stewart, L., Zemel, R.: Automated Detection of Unusual Events on Stairs. Image and Vision Computing 27, 153–166 (2009)

    Article  Google Scholar 

  4. Yin, J., Yang, Q., Junfen Pan, J.: Sensor-Based Abnormal Human-Activity Detection. IEEE Transactions on Knowledge and Data Engineering 20, 1082–1090 (2008)

    Article  Google Scholar 

  5. Dubois, A., Charpillet, F.: Human Activities Recognition with RGB-Depth Camera using HMM. In: 35th Annual International Conference on the IEEE EMBS, pp. 4666–4669 (2013)

    Google Scholar 

  6. Jiang, M., Chen, Y., Zhao, Y., Cai, A.: A Real-Time Fall Detection System Based on HMM and RVM. In: Visual Communications and Image Processing, pp. 1–6 (2013)

    Google Scholar 

  7. Patsadu, O., Nukoolkit, C., Watanapa, B.: Human Gesture Recognition Using Kinect Camera. In: Ninth International Joint Conference on Computer Science and Software Engineering, pp. 28–32 (2012)

    Google Scholar 

  8. Jalal, A., Kamal, S., Kim, D.: A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments. Sensors 14, 11735–11759 (2014)

    Article  Google Scholar 

  9. Raptis, M., Kirovski, D., Hoppe, H.: Real-Time Classification of Dance Gestures from Skeleton Animation. In: Symposium on Computer Animation, pp. 147–156 (2011)

    Google Scholar 

  10. Yamato, J., Ohya, J., Ishii, K.: Recognizing Human Action in Time-Sequential Images using Hidden Markov Model. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 379–385 (1992)

    Google Scholar 

  11. Starner, T.: Visual Recognition of American Sign Language Using Hidden Markov Models. Massachusetts Institute of Technology (1995)

    Google Scholar 

  12. Liu, T., Song, Y., Gu, Y., Li, A.: Human Action Recognition Based on Depth Images from Microsoft Kinect. In: Fourth Global Congress on Intelligent Systems, pp. 200–204 (2013)

    Google Scholar 

  13. Lai, K., Konrad, J., Ishwar, P.: A gesture-driven computer interface using Kinect. In: IEEE Southwest Symposium on Image Analysis and Interpretation, pp. 185–188 (2012)

    Google Scholar 

  14. Vemulapalli, R., Arrate, F., Chellappa, R.: Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 588–595 (2014)

    Google Scholar 

  15. Uddin, Z., Thang, D.N., Kim, T.-S.: Human Activity Recognition via 3-D Joint Angle Features and Hidden Markov Models. In: Proceedings of 2010 IEEE 17th International Conference on Image Processing, pp. 713–716 (2010)

    Google Scholar 

  16. Ji, X., Wang, C., Li, Y., Wu, Q.: Hidden Markov Model-based Human Action Recognition Using Mixed Features. Journal of Computational Information Systems, 3659–3666 (2013)

    Google Scholar 

  17. Forney, D.: The Viterbi Algorithm. Proceedings of the IEEE 61 (1973)

    Google Scholar 

  18. Kajastila, R., Hamalainen, P.: Augmented Climbing: Interacting With Projected Graphics on a Climbing Wall. In: CHI Extended Abstracts 2014, pp. 1279–1284 (2014)

    Google Scholar 

  19. Juditsky, A., Nemirovski, A.: Functional aggregation for nonparametric regression. Annals of Statistics 28(3), 681–712 (2000)

    Article  MathSciNet  Google Scholar 

  20. Wachel, P., Śliwiński, P.: Aggregative modelling of nonlinear systems. IEEE Signal Processing Letters 33(9), 1482–1486 (2015)

    Article  Google Scholar 

  21. Tsybakov, A.B.: Optimal rates of aggregation. In: Schölkopf, B., Warmuth, M.K. (eds.) COLT/Kernel 2003. LNCS (LNAI), vol. 2777, pp. 303–313. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

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Correspondence to Aleksandra Postawka .

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Postawka, A., Śliwiński, P. (2015). Recognition and Modeling of Atypical Children Behavior. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_68

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  • DOI: https://doi.org/10.1007/978-3-319-19324-3_68

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19323-6

  • Online ISBN: 978-3-319-19324-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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