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A robust method of detecting hand gestures using depth sensors

机译:使用深度传感器检测手势的可靠方法

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摘要

Depth sensors, including Kinect and Xtion, open up a new possibility for future human-computer interaction (HCI). Even though there already are some mature methods of detecting human skeleton and poses using depth sensors, it is still an unsolved problem to detect hands and recognize delicate gestures effectively, because hands are too small a part in the images generated from depth sensor, so the details of hands are hard to extract. In this paper, we present a gesture detecting method that is able to: firstly segment hands through skin color segmentation and K-means clustering; secondly find the convex hull and the contour that form the hand shape; thirdly detect positions of each fingertip; and finally represent gestures using the sets of detected hand data. Having been tested with a series of applications, our method is proved to be robust and effective.
机译:包括Kinect和Xtion在内的深度传感器为未来的人机交互(HCI)开辟了新的可能性。尽管已经有一些使用深度传感器检测人体骨骼和姿势的成熟方法,但是有效检测手并识别精细手势仍然是一个尚未解决的问题,因为手在深度传感器生成的图像中只占很小的一部分,因此手的细节很难提取。在本文中,我们提出一种手势检测方法,该方法能够:首先通过肤色分割和K均值聚类对手进行分割;其次找到形成手形的凸包和轮廓。第三,检测每个指尖的位置;最后使用检测到的手形数据表示手势。经过一系列应用程序的测试,我们的方法被证明是可靠且有效的。

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