摘要
基于视觉的手势识别是实现新一代人机交互的关键技术。从手势分割和手势表示两方面入手,提出了一种基于Open CV的多特征实时手势识别方法。利用HSV颜色空间肤色分割算法分割出肤色区域,根据手势的几何特征分离出手势区域,然后运用凸包算法检测指尖,结合指尖个数、手指间角度特征和轮廓长宽比特征,建立决策树对本定义的12种不同手势进行分类。实验结果表明,本方法具有较好的鲁棒性、实时性好、识别率高。
Computer vision-based hand gesture recognition has become a key technique in the realization of new human-computer interaction. This paper proposes a method in the recognition of real-time hand gestures with multiple cues based on OpenCV. The skin area is detected with HSV, and the hand is segmented with gesture geometric characteristics. Then the fingerti 12 different gestures defined, a your fingers ps are detected by the convex hull algorithm. For distinguishing and recognizing the decision tree is adopted combined with the number of fingers, the angle between aspect ratio features and contour features. Experimental results demonstrate that the robust and real-time, and high recognition rate and various gestures are achieved.
出处
《电子科技》
2015年第8期145-148,共4页
Electronic Science and Technology
基金
国家自然科学基金资助项目(61472256
61170277)
上海市教委科研创新重点基金资助项目(12zz137)
沪江基金资助项目(C14002)
关键词
手势识别
多特征
肤色分割
凸包算法
决策树
gesture recognition
multiple cues
skin segmentation
convex hull algorithm
decision tree
