Developing a Multiple-angle Hand Gesture Recognition System for Human Machine Interactions

This article presents a robotic visual system that allows effective recognition of multiple-angle hand gestures in finger guessing games. We shot images of hand gestures at various angles to train support vector machine (SVM) for the construction of a multiple-angle hand gesture recognition system. Our experimental results show that the hand gesture recognition system presented by this article can effectively recognize hand gestures, at over 95%, of different angles and sizes, with different ornaments, and of different skin colors, while recognizing right or left hand gestures, at up to 90% recognition rate.

[1]  Cyrus Shahabi,et al.  Device independence and extensibility in gesture recognition , 2003, IEEE Virtual Reality, 2003. Proceedings..

[2]  Shaoyan Zhang,et al.  Face recognition with support vector machine , 2003, IEEE International Conference on Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003.

[3]  Federico Girosi,et al.  Training support vector machines: an application to face detection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  Mu-Chun Su,et al.  A static hand gesture recognition system using a composite neural network , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[5]  Tsutomu Miyasato,et al.  Multi-camera hand pose recognition system using skeleton image , 1995, Proceedings 4th IEEE International Workshop on Robot and Human Communication.

[6]  JongShill Lee,et al.  Hand region extraction and gesture recognition from video stream with complex background through entropy analysis , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[8]  Ming-Hsuan Yang,et al.  Gender classification with support vector machines , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[9]  Tomaso A. Poggio,et al.  Face recognition with support vector machines: global versus component-based approach , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.