Abstract
The results of application of the neural network modules to detect the head motion parameters are presented. Each module has a very simple structure and consists of a pair of excitatory and inhibitory neurons that have common center, different sizes of their receptive fields and time delay. Detection of the initial moment of head motion was evaluated during computer simulation. To test the module performance, synthetic video facial image sequences from SYLAHP database monitoring the head motion were used. It was shown that the UE amplitude and polarity qualitatively correspond to face motion amplitude. Besides the initial front of UE quick changes corresponding to quick motion of head was equal to 12 ms in all cases (n = 46). Future steps of research and developments in this direction have been shortly discussed.
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The work is supported by the Russian Ministry for Education and Science, projects NN 2.955.2017/4.6 and 6.5961.2017/8.9.
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Shaposhnikov, D., Podladchikova, L. (2019). Detection of Initial Moment of Head Motion by Neural Network Modules. In: Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V., Tiumentsev, Y. (eds) Advances in Neural Computation, Machine Learning, and Cognitive Research II. NEUROINFORMATICS 2018. Studies in Computational Intelligence, vol 799. Springer, Cham. https://doi.org/10.1007/978-3-030-01328-8_25
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DOI: https://doi.org/10.1007/978-3-030-01328-8_25
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