DocumentCode :
691544
Title :
Dynamic Gesture Recognition Based on Fusing Frame Images
Author :
Tingfang Zhang ; Zhiquan Feng
Author_Institution :
Sch. of Inf. Sci. & Eng., Univ. of Jinan, Jinan, China
fYear :
2013
fDate :
6-7 Nov. 2013
Firstpage :
280
Lastpage :
283
Abstract :
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%.
Keywords :
gesture recognition; human computer interaction; image fusion; Hausdorff distance; density distribution features; dynamic hand gesture recognition rate; fingertip detection; frame image fusion; gesture recognition efficiency improvement; hierarchical identification model; human-computer interaction technology; rough gesture recognition; static image recognition; Dynamics; Educational institutions; Gesture recognition; Heuristic algorithms; Hidden Markov models; Human computer interaction; Image recognition; Acceleration; Gyroscope; Self- balance; the PID;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Engineering Applications, 2013 Fourth International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4799-2791-3
Type :
conf
DOI :
10.1109/ISDEA.2013.468
Filename :
6843445
Link To Document :
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