基于Kinect手势识别的应用研究

A Gesture Recognition Research and Application Based on Kinect

论文针对人机交互领域中动态手势识别问题,利用Kinect传感器获取手势的深度图像,进而追踪人体手部骨骼的关键节点。利用多项式时间算法减少了DTW算法中最佳匹配过程中的冗余计算,然后将提取的手部特征序列模板与参考序列模板进行最佳匹配,得出两序列模板之间的最优规整路径(即两序列的相似度),进而得到有效的识别结果。最后将手势识别方法运用到视力检测中,实现了基于手势的视力测试平台,改变了传统视力测试的方式,提高了人机交互的体验。

In this paper,aiming at dynamic gesture recognition in the field of human-computer interaction,Kinect sensor is used to obtain the depth of gesture images,and then track the human hand bone key nodes. The polynomial time algorithm is used to reduce the redundancy calculation in the best matching process of the DTW algorithm. Then,the extracted feature sequence template is matched with the reference sequence template,and the optimal path the similarity of the two sequences between the two sequences is obtained. And then the effective recognition results are gotten. Finally,the gesture recognition method is applied to the visual inspection to realize the gesture-based visual test platform,which changes the way of traditional vision test and improves the experience of human-computer interaction.