A Real-time Dynamic Gesture Recognition Based on 3D Trajectories in Distinguishing Similar Gestures

被引：0
|
作者：
Ding, Zeyu [1 ,2 ]
Zhang, Zexiong [1 ]
Chen, Yanmei [1 ]
Chen, Yen-Lun [1 ]
Wu, Xinyu [1 ,3 ]
机构：
[1] Chinese Acad Sci, Shenzhen Inst Adv Technol, Guangdong Prov Key Lab Robot & Intelligent Syst, Beijing 100864, Peoples R China
[2] Univ Sci & Technol China, Hefei, Peoples R China
[3] Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Hong Kong, Peoples R China
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION | 2015年
关键词：
gesture recognition; HMM; similar gesture recognition; VIDEO;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
There are many shape-similar gestures which cause errors in the process of hand gesture recognition. In this paper, a new method which can distinguish the similar gestures was proposed. The information of motion trajectory is captured by a leap motion in three-dimension space, and the orientation characteristics are quantified and coded as the feature. Then the Hidden Markov Model (HMM) algorithm is utilized to model and classify gestures. But there are many shape-similar gestures in our database (numbers 0-9 and alphabets A-Z) such as S and 5, Z and 2 whose recognition rates are low. In this paper, we proposed a new method that can distinguish the similar gestures in real-time. The experiment result demonstrates the effectiveness of the proposed method.
引用
收藏
页码：250 / 255
页数：6
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