Abstract
This chapter reviews an example of preservation and gamification scenario applied to traditional sports. In the first section, we describe a preservation technique to capture intangible content. It includes character modelling, motion recording, and animation processing. The second section is focused on the gamification aspect. It describes an interactive scenario integrated in a platform that includes a multimodal capturing system, a motion comparison and analysis, and a semantic-based feedback system.
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References
P. Ratner, 3-D Human Modeling and Animation (Wiley, New York, 2012)
B. Allen, B. Curless, Z. Popović, The space of human body shapes: reconstruction and parameterization from range scans, in ACM Transactions on Graphics (TOG), ACM, Vol. 22, No. 3, 2003, July, pp. 587–594
M. Bastioni, Ideas and methods for modeling 3D human figures The principal algorithms used by MakeHuman and their implementation in a new approach to parametric modeling, pp. 1–6
S.O. Madgwick, A.J. Harrison, R. Vaidyanathan, Estimation of imu and marg orientation using a gradient descent algorithm, in Rehabilitation Robotics (ICORR), 2011 I.E. International Conference, on IEEE, 2011, pp. 1–7
A. Ahmadi, E. Mitchell, C. Richter, F. Destelle, M. Gowing, N.E. O'Connor, K. Moran, Toward automatic activity classification and movement assessment during a sports training session. IEEE Internet Things J. 2(1), 23–32 (2015)
F. Destelle, A. Ahmadi, N.E. O’Connor, K. Moran, A. Chatzitofis, D. Zarpalas, P. Daras, Low-cost accurate skeleton tracking based on fusion of Kinect and wearable inertial sensors, in Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European, IEEE, 2014, September, pp. 371–375
A. Ahmadi, F. Destelle, D. Monaghan, K. Moran, N.E. O’Connor, L. Unzueta, M.T. Linaza, Human gait monitoring using body-worn inertial sensors and kinematic modelling, in SENSORS, 2015 IEEE, pp. 1–4
A. Savitzky, M.J. Golay, Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 36(8), 1627–1639 (1964)
D.S. Alexiadis, P. Daras, Quaternionic signal processing techniques for automatic evaluation of dance performances from MoCap data. IEEE Trans. Multimedia 16(5), 1391–1406 (2014)
Z. Wang, A.C. Bovik, H.R. Sheikh, E.P. Simoncelli, Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)
Acknowledgements
This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement FP7-601170 RePlay.
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Tisserand, Y. et al. (2017). Preservation and Gamification of Traditional Sports. In: Ioannides, M., Magnenat-Thalmann, N., Papagiannakis, G. (eds) Mixed Reality and Gamification for Cultural Heritage. Springer, Cham. https://doi.org/10.1007/978-3-319-49607-8_17
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DOI: https://doi.org/10.1007/978-3-319-49607-8_17
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