Abstract
Hand Gesture recognition systems enable people to interact with digital systems naturally. Due to the spread of body motion capture device, depth information is available for getting more delicate and effective gesture recognition results. However, due to the limitation of devices such as Microsoft Kinect, it is still very difficult to obtain hand gesture information in rela-time. This paper proposes an integrated approach of real-time hand gesture recognition based on feature points. It explains our solutions for hand segmentation and feature points abstraction based on real-time motion captured images. Having been tested with a series of applications, our method is proved to be robust and effective, and suitable for further extension in real-time hand gesture recognition systems.
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