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首页> 外文期刊>International Journal of Advanced Robotic Systems >A Kinect-based Gesture Recognition Approach for a Natural Human Robot Interface
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A Kinect-based Gesture Recognition Approach for a Natural Human Robot Interface

机译：一种基于Kinect的手势识别方法，用于自然人机器人界面

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In this paper, we present a gesture recognition system for the development of a human-robot interaction (HRI) interface. Kinect cameras and the OpenNI framework are used to obtain real-time tracking of a human skeleton. Ten different gestures, performed by different persons, are defined. Quaternions of joint angles are first used as robust and significant features. Next, neural network (NN) classifiers are trained to recognize the different gestures. This work deals with different challenging tasks, such as the real-time implementation of a gesture recognition system and the temporal resolution of gestures. The HRI interface developed in this work includes three Kinect cameras placed at different locations in an indoor environment and an autonomous mobile robot that can be remotely controlled by one operator standing in front of one of the Kinects. Moreover, the system is supplied with a people re-identification module which guarantees that only one person at a time has control of the robot. The system's performance is first validated offline, and then online experiments are carried out, proving the real-time operation of the system as required by a HRI interface.
机译：在本文中，我们提出了一种用于开发人机交互（HRI）界面的姿态识别系统。 Kinect相机和Openni框架用于获得人类骨架的实时跟踪。定义了由不同人员执行的十种不同的手势。关节角度的四分之一首先用作稳健和显着的特征。接下来，训练神经网络（NN）分类器以识别不同的手势。这项工作涉及不同的具有挑战性的任务，例如手势识别系统的实时实现和手势的时间分辨率。在本工作中开发的HRI界面包括位于室内环境中的不同位置的三个Kinect相机，可以通过站立在其中一个Kinects前方的一个操作员远程控制的自主移动机器人。此外，系统提供了一个人重新识别模块，保证只有一个人一次只控制机器人。系统的性能首先验证脱机，然后执行在线实验，从而证明系统的实时运行由HRI接口的要求。

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