基于表观的动态孤立手势识别

给出一种基于表观的动态孤立手势识别技术.借助于图像运动的变阶参数模型和鲁棒回归分析,提出一种基于运动分割的图像运动估计方法.基于图像运动参数,构造了两种表观变化模型分别作为手势的表观特征,利用最大最小优化算法来创建手势参考模板,并利用基于模板的分类技术进行识别.对120个手势样本所做的大量实验表明,这种动态孤立手势识别技术具有识别率高、计算量小、算法稳定性好等优点.

Appearance-Based Dynamic Hand Gesture Recognition from Image Sequences with Complex Background

In this paper, the authors present an appearance-based approach to dynamic hand gesture recognition. A motion-based segmentation scheme for image motion estimation is proposed using variable-order parameterized models of image motion and robust regression. Based on image motion parameters, two different appearance change models of hand gestures are created. Template-Based classification technique is then employed to perform hand gesture recognition in which reference templates are created with a mini-max type of optimization. A series of experiments on 120 image sequences show that high recognition rate, low computation load, and high stability can be achieved with the proposed methods.