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Kinect-Based Vision System of Mine Rescue Robot for Low Illuminous Environment

机译:低光照环境下基于Kinect的矿山救援机器人视觉系统

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This paper presents Kinect-based vision system of mine rescue robot working in illuminous underground environment. The somatosensory system of Kinect is used to realize the hand gesture recognition involving static hand gesture and action. AK-curvature based convex detection method is proposed to fit the hand contour with polygon. In addition, the hand action is completed by using the NiTE library with the framework of hand gesture recognition. In addition, the proposed method is compared with BP neural network and template matching. Furthermore, taking advantage of the information of the depth map, the interface of hand gesture recognition is established for human machine interaction of rescue robot. Experimental results verify the effectiveness of Kinect-based vision system as a feasible and alternative technology for HMI of mine rescue robot.
机译:本文提出了一种基于Kinect的矿井救援机器人视觉系统,该机器人可以在明亮的地下环境中工作。 Kinect的体感系统用于实现涉及静态手势和动作的手势识别。提出了一种基于AK曲率的凸检测方法,以使手部轮廓具有多边形。此外,通过使用具有手势识别框架的NiTE库来完成手势操作。另外,将该方法与BP神经网络和模板匹配进行了比较。此外,利用深度图的信息,为救援机器人的人机交互建立了手势识别界面。实验结果证明了基于Kinect的视觉系统作为矿山救援机器人人机界面的一种可行的替代技术的有效性。

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