Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Study on Real-time Gesture Recognition based on Convolutional Neural Network for Game Applications

게임 어플리케이션을 위한 컨볼루션 신경망 기반의 실시간 제스처 인식 연구

  • Chae, Ji Hun (Dept. of Computer Engineering, Graduate School, Keimyung University) ;
  • Lim, Jong Heon (Dept. of Computer Engineering, Graduate School, Keimyung University) ;
  • Kim, Hae Sung (Faculty of Computer Engineering, Keimyung University) ;
  • Lee, Joon Jae (Faculty of Computer Engineering, Keimyung University)
  • Received : 2017.04.05
  • Accepted : 2017.04.21
  • Published : 2017.05.31
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Abstract

Humans have often been used gesture to communicate with each other. The communication between computer and person was also not different. To interact with a computer, we command with gesture, keyboard, mouse and extra devices. Especially, the gesture is very useful in many environments such as gaming and VR(Virtual Reality), which requires high specification and rendering time. In this paper, we propose a gesture recognition method based on CNN model to apply to gaming and real-time applications. Deep learning for gesture recognition is processed in a separated server and the preprocessing for data acquisition is done a client PC. The experimental results show that the proposed method is in accuracy higher than the conventional method in game environment.

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References

  1. H. Cheng, L. Yang, and Z. Liu, "Survey on 3D Hand Gesture Recognition," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 26, No. 9, pp. 1659-1673, 2016. https://doi.org/10.1109/TCSVT.2015.2469551
  2. J. Schmidhuber, "Deep Learning in Neural Networks: An Overview," Neural Networks, Vol. 61, pp. 85-117, 2015. https://doi.org/10.1016/j.neunet.2014.09.003
  3. J.H. Chae, J.H. Lim, and J.J. Lee "Gesture Classification Based on k-Nearest Neighbors Algorithm for Game Interface," Journal of Korea Multimedia Society, Vol. 19, No. 5, pp. 874-880, 2016. https://doi.org/10.9717/kmms.2016.19.5.874
  4. B. Fasel and D. Gatica-Perez, "Rotation-Invariant Neoperceptron," Proceeding of 18th International Conference on Pattern Recognition, pp. 336-339, 2006.
  5. R. McCartney, J. Yuan, and H.P. Bischof, "Gesture Recognition with the Leap Motion Controller," Proceeding of International Conference on Image Processing, Computer Vision, and Pattern Recognition, pp. 3-9, 2015.
  6. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, "Gradient-based Learning Applied to Document Recognition," Proceedings of the IEEE, Vol. 86, No. 11, pp. 2278-2324, 1998. https://doi.org/10.1109/5.726791
  7. G.E. Dahl, T.N. Sainath, and G.E. Hinton, "Improving Deep Neural Networks for LVCSR Using Rectified Linear Units and Dropout," Proceeding of IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 8609-8613, 2013.
  8. Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, et. al, "Caffe: Convolutional Architecture for Fast Feature Embedding," Proceeding of ACM International Conference on Multimedia, pp. 675-678, 2014.
  9. M. Gori and A. Tesi, "On the Problem of Local Minima in Backpropagation," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, No. 1, pp. 76-86, 1992. https://doi.org/10.1109/34.107014
  10. R.D. Vatavu, L. Anthony, and J.O. Wobbrock, "Gestures as Point Clouds: A $P Recognizer for User Interface Prototypes," Proceeding of ACM International Conference on Multimodal Interaction, pp. 273-280, 2012.
  11. J.H. Lim, J.H. Chae, H.S. Kim, H.K. Park, and J.J. Lee, "Study on VR Game for Rehabilitation Using Realtime Gesture Recognition," Proceeding of Korea Information and Communication Society Winter Conference, pp. 534-535, 2017.

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