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A Real-Time Hand Gesture Recognition Approach Based on Motion Features of Feature Points

机译:基于特征点的运动特征的实时手势识别方法

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Dynamic hand gesture recognition enables people to communicate with computers naturally without any mechanical devices. Due to the spread of depth sensor such as Microsoft Kinect and Leap Motion, dynamic hand gesture recognition becomes possible for recognizing meticulous gesture information in real time. However, most of these methods recognize the hand gesture by fuzzy features such as contour size, which cause imprecise hand gesture recognition. This paper presents a precise tracing of feature points including palm center, fingertips and joints by using Kinect. A novel recognition method based on precise motion features of these feature points is also presented. Having been tested with a series of applications, our method is proved to be robust and effective, and suitable for further application in real-time HCI systems.
机译:动态手势识别使人们能够自然地与计算机通信,而没有任何机械设备。 由于深度传感器如Microsoft Kinect和Leap Motion的传播,动态手势识别可以实时识别细致的手势信息。 然而,大多数方法通过诸如轮廓尺寸的模糊特征识别手势,这导致不精确的手势识别。 本文介绍了通过使用Kinect的特征点的精确追踪,包括掌心,指尖和关节。 还呈现了基于这些特征点的精确运动特征的新颖识别方法。 通过一系列应用进行了测试,我们的方法被证明是强大而有效的,适用于实时HCI系统中的进一步应用。

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