Temporal data processing from webcam eye tracking using artificial neural networks

Malakhova, E.Y., Shelepin, E.Y., Malashin, R.O.

Full text «Opticheskii Zhurnal»

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Publication in Journal of Optical Technology

For Russian citation (Opticheskii Zhurnal):

Малахова Е.Ю., Шелепин Е.Ю., Малашин Р.О. Применение искусственных нейронных сетей, учитывающих временную динамику, для анализа движения глаз без специального оборудования // Оптический журнал. 2018. Т. 85. № 3. С. 77–80. http://doi.org/10.17586/1023-5086-2018-85-03-77-80

Malakhova E.Yu., Shelepin E.Yu., Malashin R.O. Temporal data processing from webcam eye tracking using artificial neural networks [in Russian] // Opticheskii Zhurnal. 2018. V. 85. № 3. P. 77–80. http://doi.org/10.17586/1023-5086-2018-85-03-77-80

For citation (Journal of Optical Technology):

E. Yu. Malakhova, E. Yu. Shelepin, and R. O. Malashin, "Temporal data processing from webcam eye tracking using artificial neural networks," Journal of Optical Technology. 85(3), 186-188 (2018). https://doi.org/10.1364/JOT.85.000186

Abstract:

The technology for determining eye gaze direction on a monitor screen is considered by analyzing the images received from a video camera directed at a user without using additional equipment. We propose a combined convolutional neural network extracting high-level features of images with a neural network of long short-term memory that takes into account the temporal dynamics of oculomotor activity. To train the model, a representative database of video sequences with reference information concerning eye direction was collected. Experiments confirmed that accounting for temporal information increased the accuracy of recording the eye direction.

Keywords:

еye tracking, artificial neural networks, video sequences analysis

OCIS codes: 150.0150

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