基于支持向量机数据分析红外手势识别方法研究

该文提出了利用支持向量机结合仿生六点手势模型优化红外体感控制设备手势识别的方法。采集空间手势信息,仿生六点手势模型提取手势特征向量,利用支持向量机分类及校对数据,引用核函数将低维空间不可分信息映射至高维空间实现线性可分。结果表明,运用基于支持向量机的红外体感设备手势方法能有效识别手势,减轻计算机通信的传输负荷。

Study on Infrared Hand Gesture Recognition Based on Support Vector Machine Algorithm

A method of using the support vector machine combining with the bionic-six-hand models to optimize infrared motion control apparatus gesture recognition is proposed in this paper. The space gesture information is collected, then the gesture eigenvector is extracted by the bionic-six-hand models, and the support vector machine is used for the classification and proofread of the data, the kernel function is introduced to map the low-dimensional space un-separable information into the high-dimensional space to realize detachable linearity. The experimental results show that the infrared somatosensory device using the support vector machine algorithm can recognize the hand gestures effectively and reduce the load of communication transmission.