基于Leap Motion的三维手势交互系统研究

手势识别的快速发展及体感设备的不断更新为三维手势交互提供了灵感，基于Leap Motion 手势识别和最邻近算法，建立了一种三维手势交互系统。首先对手势设计理论和交互手 势设计原则进行研究，基于此设计手势功能和建立手势库，并将手势库分为 8 种手势；其次进 行手势特征提取，建立手指关键点模型，获取手势特征的角度特征；然后计算 KNN 算法和 SVM 算法的手势识别效率，KNN 改进算法取得较好的识别效率；最后，设计三维交互系统，手势分 类为 4 个模块，每个模块有 2 个手势任务；20 名测试者中提取 1 600 组手势数据，并进行总采 集样本关节点均值的数据分析；设计三维交互系统模块，在 Unity3D 中创建的三维交互系统中 导入 1 600 组手势数据，根据自定义的 8 种手势驱动虚拟手完成交互设计过程，完成用户体验 分析和手势识别效率统计。通过研究发现，基于 Leap Motion 手势识别具有较高的识别效率， 三维手势交互系统富有创新性。

Research on 3D Gesture Interaction System Based on Leap Motion

The rapid development of gesture recognition and the continuous updating of somatosensory devices provide inspiration for 3D gesture interaction; based on Leap Motion gesture recognition and nearest neighbor algorithms, a 3D gesture interaction system is established. Firstly, the theory of gesture design and the theory of interactive gesture design are studied. Based on this, the gesture function and gesture library are designed, and the gesture library is divided into eight gestures. Secondly, the gesture feature extraction is performed to establish the finger key point model and obtain the angle of the gesture feature; then calculate the gesture recognition efficiency of KNN algorithm and SVM algorithm, and KNN improved algorithm achieves better recognition efficiency. Finally, a 3D interactive system is designed, and the gesture is classified into 4 modules, each module having two gesture tasks; 20 people are gathered to extract 1 600 sets of gesture data, and a data analysis of the total sample joint point mean value is conducted. Design a 3D interactive system module, and import 1 600 sets of gesture data in the 3D interactive system created in Unity3D; the interactive design process, user experience analysis and gesture recognition efficiency statistics are completed according to the customized eight gesture driven virtual hands. Through research, it is found that Leap Motion gesture recognition has high recognition efficiency, and the three-dimensional gesture interaction system is fairly innovative.