摘要
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 12 0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 .
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.
出处
《软件学报》
EI
CSCD
北大核心
2000年第1期54-61,共8页
Journal of Software
基金
国家 8 6 3高科技项目基金! (No.86 3- 30 6 - 0 3- 0 1)资助
关键词
计算机视觉
手势识别
图像运动模型
表观
Computer vision, human computer interface, hand gesture recognition, image motion model, robust regression, dynamic programming matching.
