Hand Gesture Recognition Using T-CombNET : A New Neural Network Model

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概要

• 論文の詳細を見る

• This paper presents a new neural network structure, called Temporal-CombNET (T-CombNET), dedicated to the time series analysis and classification. It has been developed from a large scale Neural Network structure, CombNET-II, which is designed to deal with a very large vocabulary, such as Japanese character recognition. Our specific modifications of the original CombNET-II model allow it to do temporal analysis, and to be used in large set of human movements recognition system. In T-CombNET structure one of most important parameter to be set is the space division criterion. In this paper we analyze some practical approaches and present an Interclass Distance Measurement based criterion. The T-CombNET performance is analyzed applying to in a practical problem, Japanese Kana finger spelling recognition. The obtained results show a superior recognition rate when compared to different neural network structures, such as Multi-Layer Perceptron, Learning Vector Quantization, Elman and Jordan Partially Recurre Neural Networks, CombNET-II, k-NN, and the proposed T-CombNET structure.

• 社団法人電子情報通信学会の論文
• 2000-11-25

著者

• Bhuiyan Md.shoaib

  The Author Is With The Information Processing Center Suzuka University Of Medical Science And Techno

• Iwata Akira

  The Authors Are With The Department Of Electrical And Computer Engineering Nagoya Institute Of Techn

• LAMAR Marcus

  The authors are with the Department of Electrical and Computer Engineering, Nagoya Institute of Tech

• Lamar Marcus

  The Authors Are With The Department Of Electrical And Computer Engineering Nagoya Institute Of Techn

関連論文

• Hand Gesture Recognition Using T-CombNET : A New Neural Network Model

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