DocumentCode :
1716703
Title :
Gesture recognition based on improved shape context algorithm and Earth Mover´s Distance
Author :
Ma Li-ling ; Cheng Cheng ; Zhang Shu-fen ; Wang Jun-zheng
Author_Institution :
Autom. Sch., Beijing Inst. of Technol., Beijing, China
fYear :
2013
Firstpage :
3906
Lastpage :
3911
Abstract :
The common shape context algorithm does not have the rotational invariance property, which makes the characteristic extraction accuracy decreased a lot under some circumstances. A new improved shape context algorithm is proposed to solve this problem in this paper. The new algorithm chooses some key points and uses them as reference points, rather than like the traditional way that relies on all the contour information. Such improvement can make the new shape context algorithm rotation-invariant and can also simplify the original algorithm. Besides, another improvement is made in this paper. We combine shape context algorithm with EMD to create a new recognition method. The method is used for gesture recognition, and the experiment result shows that the new method has enhanced the gesture recognition accuracy a lot.
Keywords :
gesture recognition; human computer interaction; statistical analysis; EMD; Earth mover´s distance; characteristic extraction accuracy; gesture recognition; gesture recognition accuracy enhancement; key points; reference points; rotation-invariant shape context algorithm; Context; Gesture recognition; Histograms; Human computer interaction; Image color analysis; Quantization (signal); Shape; EMD; Gesture Recognition; invariance; shape context;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
Type :
conf
Filename :
6640102
Link To Document :
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