DocumentCode :
3351803
Title :
Application of gesture recognition based on simulated annealing BP neural network
Author :
Hui Zhang ; Yongqi Wang ; Chen Deng
Author_Institution :
Dept. of Comput. Sci., Shanghai Univ. of Eng. Sci., Shanghai, China
Volume :
1
fYear :
2011
fDate :
12-14 Aug. 2011
Firstpage :
178
Lastpage :
181
Abstract :
In this paper, an algorithm of gesture recognition based on simulated annealing BP neural network is presented. Firstly, this new algorithm extracts the edge outline by skin color division and recognition feature of the distance between center and edge of binary gesture image. Secondly, it combines simulated annealing with BP neural network, which has both the learning ability and robustness of the neural network and the global optimization of simulated annealing, avoids the slow convergence and prevents it from falling into local minimum. The results of experiments show that the algorithm can greatly improve efficiency and accuracy of gesture recognition.
Keywords :
backpropagation; edge detection; gesture recognition; image colour analysis; neural nets; simulated annealing; backpropagation; binary gesture image; edge outline extraction; gesture recognition; global optimization; learning ability; simulated annealing BP neural network; skin color division; skin recognition feature; Biological neural networks; Feature extraction; Gesture recognition; Image color analysis; Image edge detection; Simulated annealing; Training; BP neural network; gesture recognition; simulated annealing; skin color division;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
Type :
conf
DOI :
10.1109/EMEIT.2011.6022891
Filename :
6022891
Link To Document :
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