Title :
Hand gesture recognition using morphological principal component analysis and an improved CombNET-II
Author :
Lamar, Marcus V. ; Bhuiyan, Md Shoaib ; Iwata, Akira
Author_Institution :
Dept. of Electr. & Comput. Eng., Nagoya Inst. of Technol., Japan
Abstract :
A new neural network structure dedicated to time series recognition, T-CombNET, is presented. The model is developed from a large scale neural network CombNet-II, designed to deal with a very large vocabulary for character recognition. Our specific modifications of the original CombNet-II model allows it to do temporal analysis, and to be used in a large set of human movement recognition systems. This paper also presents a feature extraction method based on morphological principal component analysis that completely describes a hand gesture in 2-dimensional time varying vector. The proposed feature extraction method along with the T-CombNET structure were then used to develop a complete Japanese Kana hand alphabet recognition system consisting of 42 static postures and 34 hand motions. We obtained a superior recognition rate of 99.4% in the gesture recognition experiments when compared to different neural network structures like multi-layer perceptron, learning vector quantization (LVQ), Elman and Jordan partially recurrent neural networks, CombNET-II and the proposed T-CombNET structure
Keywords :
character recognition; feature extraction; gesture recognition; neural nets; principal component analysis; time series; 2D time varying vector; CombNET-II; Japanese Kana alphabet recognition; character recognition; experiments; feature extraction; hand gesture recognition; human movement recognition systems; large vocabulary; learning vector quantization; morphological principal component analysis; multi-layer perceptron; neural network structure; partially recurrent neural networks; temporal analysis; time series recognition; Character recognition; Feature extraction; Large-scale systems; Multi-layer neural network; Multilayer perceptrons; Neural networks; Principal component analysis; Recurrent neural networks; Vector quantization; Vocabulary;
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-5731-0
DOI :
10.1109/ICSMC.1999.812376
