利用双目视觉视频的实时三维裸手手势识别

Real-time 3D bare-hand gesture recognition using binocular vision videos

为了解决三维裸手手势识别算法识别率低、易受类肤色物体干扰的问题,提出一种利用双目视觉视频的三维裸手手势识别算法.首先依据双目视觉原理推导出三维空间内手势深度与手势面积的关系,基于此关系对三维手势进行快速识别.为进一步降低算法复杂度,根据极线约束规则提出一种只计算手势质心匹配点的立体匹配算法.实验结果表明,与现有算法相比,所提算法性能在处理速度、识别准确率、鲁棒性方面均有明显提高.同时,提出的算法具有较强的开放性,可进一步根据需求定义、添加需识别的三维手势.

Current bare-hand based gesture recognition algorithms generally have the problems of low recognition accuracy and being prone to be affected by skin-like objects.In this paper,a 3D bare-hand gesture recognition algorithm is proposed using binocular vision videos.Firstly,a relationship between the depth and area of the gesture is achieved according to the principle of binocular vision,on the basis of which fast 3D gesture recognition is realized.To further speed up the method,a fast stereo matching algorithm is proposed following the epipolar line constraint rule,which regards the gesture’s centroid as the matching point.Experimental results have demonstrated that compared with existing algorithms the proposed algorithm significantly improves the performance in processing speed, recognition accuracy, and robustness.It should be noted that the proposed algorithm is open,where more 3D gestures can be easily added upon requirement.