应用于虚拟现实人机交互系统的手势检测与跟踪研究

摘要

随着虚拟现实技术的应用范围不断扩大,人机交互系统的重要性日益突出.在人机交互系统中较为关键的指标就是手势检测与跟踪的准确度.因此,提出了一种适用于虚拟现实人机交互系统的手势检测与跟踪算法.首先采用基于手势轮廓模型的检测算法来实现手势检测,有效提高了手势检测的鲁棒性.然后采用状态空间概率预测来实现手势跟踪.此外,采用了训练后的贝叶斯分类器对待检测手势图像进行分类.实验结果显示相比传统算法,提出的算法具有较高的实时性、准确性和鲁棒性,能够有效识别运动手势,满足了人机交互的要求.%With the expanding application of virtual reality technology,the importance of human-computer interaction system has become increasingly prominent.The key index in the human-computer interaction system is the accuracy of gesture detection and tracking.Therefore,a gesture detection and tracking algorithm suitable for virtual reality human-computer interaction system is proposed in this paper.Firstly,based on the gesture contour model the gesture detection is used to detect the gesture,which improves the robustness of gesture detection effectively.Then the state space probability prediction is used to implement the gesture tracking.In addition,a trained Bayesian classifier is used to classify the gesture images to be detected.The experimental results show that,as compared with the traditional algorithm,the proposed algorithm has high real-time,accuracy and robustness,and it can effectively identify the movement gesture to meet the requirements of human-computer interaction.