Real-Time 3D Hand Gesture Recognition from Depth Image

Abstract:

In this paper, we propose a novel real-time 3D hand gesture recognition algorithm based on depth information. We segment out the hand region from depth image and convert it to a point cloud. Then, 3D moment invariant features are computed at the point cloud. Finally, support vector machine (SVM) is employed to classify the shape of hand into different categories. We collect a benchmark dataset using Microsoft Kinect for Xbox and test the propose algorithm on it. Experimental results prove the robustness of our proposed algorithm.

• Periodical: Advanced Materials Research (Volumes 765-767)
• Pages: 2826-2829
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.765-767.2826
• Online since: September 2013
• Authors: Song Lin, Rui Min Hu, Yu Lian Xiao, Li Yu Gong
• Keywords: 3D Image Processing, Depth Images, Hand Gesture Recognition, Human-Computer Interaction (HCI), KINECT

References

[1] V. I. Pavlovic, R. Sharma and T. S. Huang, Visual interpretation of hand gestures for human-computer interaction: a review. IEEE Transaction on Pattern Analysis and Machine Intelligence, 19(7), 677-695, (1997).

DOI: 10.1109/34.598226

[2] A. Just and S. Marcel, A comparative study of two state-of-the-art sequence processing techniques for hand gesture recognition. Computer Vision and Image Understanding, 113(4): 532-543, 2009.

DOI: 10.1016/j.cviu.2008.12.001

[3] B. Ionescu, D. Coquin, P. Lambert and V. Buzuloiu, Dynamic hand gesture recognition using the skeleton of the hand. EURASIP Journal of Applied Signal Processing, 2005: 2101-2109, (2005).

DOI: 10.1155/asp.2005.2101

[4] R. Kjeldsen and J. Kender, Toward the use of gesture in traditional user interfaces, in Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, Killington, VT, USA, (1996).

DOI: 10.1109/afgr.1996.557257

[5] K. Imagawa, S. Lu and S. Igi, Color-based hands tracking system for sign language recognition, in IEEE International Conference on Automatic Face and Gesture Recognition, Nara, Japan, (1998).

DOI: 10.1109/afgr.1998.670991

[6] C. Manresa, J. Varona, R. Mas and F. Perales, Hand tracking and gesture recognition for human-computer interaction. Electron Letter of Computer Vision and Image Analysis, 5(3): 96-104, (2005).

DOI: 10.5565/rev/elcvia.109

[7] T.B. Moeslund, A. Hilton and V. Kruger, A survey of advances in vision-based human motion capture and analysis. Computer Vision and Image Understanding, 104(2-3): 90-126, (2006).

DOI: 10.1016/j.cviu.2006.08.002

[8] D. J. Sturman and D. Zelter, A survey of glove-based Input. IEEE Computer Graphics and Applications. 14(1): 30-39, (1994).

DOI: 10.1109/38.250916

[9] R.Y. Wang and J. Popovic, Real-time hand-tracking with a color glove. ACM Transaction on Graphics. 28(3): 1-8, (2009).

[10] PrimeSensor http: /www. primesense. com.

[11] F. A. Sadjadi and E. L Hall. Three-dimensional moment invariants. IEEE Trans. on Pattern Analysis and Machine Intelligence. 2(2), pp.127-136, March (1980).

DOI: 10.1109/tpami.1980.4766990

[12] C. -C. Chang and C. -J. Lin. LIBSVM : a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2: 27: 1-27: 27, (2011).

DOI: 10.1145/1961189.1961199