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Classification of Skeletal Wireframe Representation of Hand Gesture Using Complex-Valued Neural Network

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Abstract

Complex-valued neural networks (CVNNs), that allow processing complex-valued data directly, have been applied to a number of practical applications, especially in signal and image processing. In this paper, we apply CVNN as a classification algorithm for the skeletal wireframe data that are generated from hand gestures. A CVNN having one hidden layer that maps complex-valued input to real-valued output was used, a training algorithm based on Levenberg Marquardt algorithm (CLMA) was derived, and a task to recognize 26 different gestures that represent English alphabet was given. The initial image processing part consists of three modules: real-time hand tracking, hand-skeletal construction, and hand gesture recognition. We have achieved; (1) efficient and accurate gesture extraction and representation in complex domain, (2) training of the CVNN utilising CLMA, and (3) providing a proof of the superiority of the aforementioned methods by utilising complex-valued learning vector quantization. A comparison with real-valued neural network shows that a CVNN with CLMA provides higher recognition performance, accompanied by significantly faster training. Moreover, a comparison of six different activation functions was performed and their utility is argued.

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Acknowledgments

This study was supported by grants to K.M. from Japanese Society for Promotion of Sciences and Technology, and the University of Fukui.

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Authors and Affiliations

  1. Graduate School of Engineering, University of Fukui, Fukui, Japan

    Abdul Rahman Hafiz & Ahmed Yarub Al-Nuaimi

  2. Department of Computer Science and Engineering, Khulna University of Engineering and Technology, Khulna, Bangladesh

    Md. Faijul Amin

  3. Graduate School of Engineering, Research and Education Program for Life Science, University of Fukui, Fukui, Japan

    Kazuyuki Murase

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  1. Abdul Rahman Hafiz
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  2. Ahmed Yarub Al-Nuaimi
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  3. Md. Faijul Amin
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  4. Kazuyuki Murase
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Correspondence to Kazuyuki Murase.

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Hafiz, A.R., Al-Nuaimi, A.Y., Amin, M.F. et al. Classification of Skeletal Wireframe Representation of Hand Gesture Using Complex-Valued Neural Network. Neural Process Lett 42, 649–664 (2015). https://doi.org/10.1007/s11063-014-9379-0

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  • DOI: https://doi.org/10.1007/s11063-014-9379-0

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