Open Access
Issue
MATEC Web of Conferences
Volume 56, 2016
2016 8th International Conference on Computer and Automation Engineering (ICCAE 2016)
Article Number 02011
Number of page(s) 4
Section Image Processing and Application
DOI https://doi.org/10.1051/matecconf/20165602011
Published online 26 April 2016
  1. A. Valli, The Design of Natural Interaction,” Multimedia Tool Applications, 38(3), pp. 295–305 (2008) [CrossRef] [Google Scholar]
  2. J. Calle, P. Martínez, D. Del Valle, and D. Cuadra, Towards the achievement of natural interaction, Engineering the User Interface, Springer, London, pp. 1–9 (2009) [CrossRef] [Google Scholar]
  3. A. Del Bimbo, Special issue on natural interaction, Multimedia Tools and Applications, 38(3), pp. 293–294 (2008) [CrossRef] [Google Scholar]
  4. W. Xu and E. J. Lee, Human-Computer Natural User Interface Based on Hand Motion Detection and Tracking, J. of Korea Multimedia Society, 15(4), pp. 501–507 (2012) [CrossRef] [Google Scholar]
  5. R. Stiefelhagen, J. Yang, and A. Waibel, A model-based gaze tracking system, Int. J. on Artifical Intelligence Tools, 6(2), pp. 193–209 (1997) [CrossRef] [Google Scholar]
  6. E. Murphy-Chutorian and M. M. Trivedi, Head pose estimation in computer vision: A survey, IEEE Trans. on Pattern Analysis and Machine Intelligence, 31(4), pp. 607–626 (2009) [CrossRef] [Google Scholar]
  7. H. Kim, S. H. Lee, M. K. Sohn, and D. J. Kim, Illumination invariant head pose estimation using random forests classifier and binary pattern run length matrix, Human-centric Computing and Information Science, 4(9), pp. 1–12 (2014) [CrossRef] [Google Scholar]
  8. H. Kim, M. K. Sohn, D. J. Kim, and N. Ryu, User’s Gaze Tracking System and Its Application Using Head Pose Estimation, IEEE Int. Conf. on Artificial Intelligence, Modelling and Simulation, pp. 166–171 (2014) [Google Scholar]
  9. A. I. Maqueda, C. R. del-Blanco, F. Jaureguizar, and N. García, Human–computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns. Computer Vision and Image Understanding, 141, pp. 126–137 (2015) [CrossRef] [Google Scholar]
  10. L. Breiman, Random forests, Machine learning, 45(1), pp.5–32 (2001.) [Google Scholar]
  11. http://openni.ru/files/handgket/index.html [Google Scholar]

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