Real-Time 3D Hand Gesture Recognition from Depth Image

DOI

10.2991/icsem.2013.242How to use a DOI?

Keywords

Hand Gesture Recognition, 3D Image Processing, Depth Images, Kinect, Human Computer Interaction

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lin Song
AU  - Ruimin Hu
AU  - Yulian Xiao
AU  - Liyu Gong
PY  - 2013/04
DA  - 2013/04
TI  - Real-Time 3D Hand Gesture Recognition from Depth Image
BT  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 1134
EP  - 1137
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.242
DO  - 10.2991/icsem.2013.242
ID  - Song2013/04
ER  -