基于Kinect手势识别的应用与研究

为解决当前智能家居系统操作繁琐的问题,同时为获得更简单的控制方式,并增加用户的体验感受,研究了基于Kinect骨骼信息的手势识别技术,并将其融入至智能家居的人机交互系统中。在该系统中,用户可以自定义手势动作或语音实现家居设备的智能控制。使用了一种基于加权动态时间规整的模板匹配手势识别算法。通过Kinect的深度摄像头获取手势深度图像和骨骼图像数据,并采用加权动态时间规整算法进行识别。实验表明使用该算法实现手势识别是可行且有效的,且其最佳识别位置是在Kinect的正前方2～2.5m处,识别准确率达到96%左右。

Application and Research on Gesture Recognition by Kinect Sensors

In order to solve the problems of complex operations in the current smart home system and acquire a simple control method and increase feeling experience for users,the gesture recognition methods based on Kinect were researched and integrated into the human-computer interaction (HCI) system in smart home.In this system,users can customize the gestures to realize the intelligent control of household equipment.The utilized template matching gesture recognition method is accomplished based on the dynamic time warping (DTW) algorithm.It employs the Kinect depth camera to obtain the skeleton depth images and gestures.The results of actual gesture recognition experiments show that the gesture recognition based on DTW algorithm is feasible and effective.The best identification distance is in range of 2-2.5 m in front of Kinect and the highest recognition accuracy can reach 96%.