Desktop Gestures Recognition for Human Computer Interaction

被引：1

作者：

Zhu, Qingjie ^{[1
,2
,6
]}

Pan, Hang ^{[3
,4
,6
]}

Yang, Minghao ^{[6
]}

Zhan, Yongsong ^{[5
]}

机构：

[1] Guilin Univ Elect Technol, Guangxi Key Lab Trusted Software, Guilin 541004, Guangxi, Peoples R China

[2] Guilin Univ Elect Technol, Guangxi Cooperat Innovat Ctr Cloud Comp & Big Dat, Guilin 541004, Guangxi, Peoples R China

[3] Guilin Univ Elect Technol, Guangxi Key Lab Cryptog & Informat Secur, Guilin 541004, Guangxi, Peoples R China

[4] Guilin Univ Elect Technol, Guangxi Coll & Univ Key Lab Intelligent Proc Comp, Guilin 541004, Guangxi, Peoples R China

[5] Guilin Univ Elect Technol, Key Lab Cloud Comp & Complex Syst, Guilin 541004, Guangxi, Peoples R China

[6] Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China

来源：

ADVANCES IN SWARM INTELLIGENCE, ICSI 2017, PT II | 2017年 / 10386卷

关键词：

Gesture recognition; Human-computer interaction; Computer vision;

D O I：

10.1007/978-3-319-61833-3_61

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A dynamic gesture recognition and understanding method in natural human-computer interaction under desktop environment is proposed, including the "reach", "take up", "move", "put down", "return", "point" and other natural interactive gestures. In preprocess procedure of each frame of the video, the Gaussian background model and HSV skin-color model is employed to remove background and segment hand gestures. The temporal and spatial information of multi frame images is combined to construct temporal and spatial features of dynamic gestures images. Then a convolution neural network is built for recognize the dynamic characteristics of gesture image. Finally, the classification result is denoised to achieve the robust recognition and understanding of gestures. Experimental results show that the proposed method has a good ability of recognizing and understanding the dynamic gestures in the desktop environment.

引用

页码：578 / 585

页数：8

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