Dynamic Gesture Recognition Based on Fusing Frame Images

被引:5
|
作者
Zhang, Tingfang [1 ,2 ]
Feng, Zhiquan [1 ,2 ]
机构
[1] Univ Jinan, Sch Informat Sci & Engn, Jinan 250022, Shandong, Peoples R China
[2] Shandong Prov Key Lab Network based Intelligent C, Jinan 250022, Peoples R China
基金
中国国家自然科学基金;
关键词
human-computer interaction; dynamic gesture recognition; Fusing Frame Images;
D O I
10.1109/ISDEA.2013.468
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the rapid development of human-computer interaction technology, gesture recognition becomes one of the key technologies of human-computer interaction. In this paper, we propose a new method of dynamic hand gestures recognition. The method adopts the hierarchical identification model for dynamic hand gestures recognition. First, we combine frame fusion with density distribution features for rough gesture recognition, second, we use the hausdorff distance or fingertip detection for accurate gesture recognition. The main innovation of this method lies in that we change the way of dynamic gestures recognition into the recognition of static image, improves the efficiency of gesture recognition effectively. Experimental results showed that our recognition rate is above 90%.
引用
收藏
页码:280 / 283
页数:4
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