摘要
为提升人机交互真实性与沉浸感,实现人手直接参与交互的目的,采用Aiolos库与朴素贝叶斯算法追踪的方法,获取手部数据驱动虚拟手。通过Kinect获取深度图像与骨架信息等原始数据,以校准方程和最小二乘法对原始数据标定,结合Aiolos库与朴素贝叶斯算法追踪手部数据,经指数平滑后跨平台传输的数据流与TransformBone控制器绑定虚拟手骨骼,最终获得利用手部追踪数据驱动虚拟手的结果。提出的虚拟手驱动方式与受限的传统交互方式相比,可发挥人手多自由度优势,对于虚拟现实研究中交互性与沉浸感的提高具有重要意义。
In order to improve the authenticity and immersion of human-computer interaction and realize the direct participation of human hand,Aiolos library and Naive Bayes algorithm were utilized to track data and to drive virtual hand based on Kinect depth data.Raw data such as depth image and skeleton information were obtained through Kinect,which were calibrated by the calibration equation and least square method.By combining Aiolos library with naive Bayes algorithm,the hand data were tracked and exponentially smoothed.The data stream bounded to the skeleton with the Transform Bone controller and transmitted across the platforms.Finally,the result of using hand tracking data to drive virtual hand was obtained.Compared with the traditional interaction constraints,the method of driving virtual hand proposed in this paper can provide complete flexibility to the multi-degree freedom of human hand,which is of great significance to the improvement of interactivity and immersion especially in the area of virtual reality.
引文
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