基于特征线条的手势识别

单目视觉的手势识别系统,通常把人手建模成一个像素或者一块,从整体上分析手势的运动参数并提取表观特征.从细微之处着手,融合颜色、运动和边缘等多种信息以提取能够反应人手结构特性的特征线条,并将特征线条分割成小的曲线段,跟踪这些曲线段的运动.采用平面模型对手势图像表观的变化建模,根据各个曲线段的运动,融合成手的整体运动分量.同时分析了图像坐标系的选取和对运动参数的影响,提出了随手运动的坐标系,以抽取平移不变的平面模型参数,进行手势识别.

Hand Gesture Recognition Based on Characteristic Curves

Monocular hand gesture recognition systems usually model a human hand as a pixel or a blob by which the motion of the whole hand are analyzed and the appearance features are extracted. But the system presented in this paper begins with the motion of a hand's local parts. Firstly by fusing on multiple information including motion, color and edge, the characteristic curves that can represent the structure of a hand are obtained. The characteristic curves are cut into short segments with the equal length, which,which are easily analyzed and and tracked.Then the planar model is adopted to model the appearance change between the consecutive images and calculated by motion of the short segments.At last,the deviation caused bu the coordinate system is also analyzed and a moving coordinate system is set up,from which translation-independent parameters of the planar model are exrtactrd for hand gesture recognition.