Formation of an algorithm for determining the degree of human involvement based on the analysis of the movement of the pupils of the operator and data on the position of the head and body

Evgenii Semenishchev; Marina Zhdanova; Aleksandr Zelensky; Inessa Gracheva; Daniil Lyakhov; Nikita Mitugov; Viacheslav Voronin

doi:10.1117/12.2666763

13 June 2023 Formation of an algorithm for determining the degree of human involvement based on the analysis of the movement of the pupils of the operator and data on the position of the head and body

Evgenii Semenishchev, Marina Zhdanova, Aleksandr Zelensky, Inessa Gracheva, Daniil Lyakhov, Nikita Mitugov, Viacheslav Voronin

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Proceedings Volume 12528, Real-Time Image Processing and Deep Learning 2023; 125280F (2023) https://doi.org/10.1117/12.2666763
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

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Abstract

The article proposes an algorithm for processing parallel analysis of visual data obtained by a machine vision system, recorded information in the human visible spectrum, and information received by a range camera. An algorithm for the formation of stable features as elements of the human body, head and pupils of a person and parallel tracking of their increment is proposed. To highlight trend lines in element displacement and eliminate the high frequency component based on a combined criterion. The image is preliminarily processed to reduce the effect of the noise component based on a multi-criteria objective function. As test data used to evaluate the effectiveness, a video stream with a resolution of 1024x768 (8-bit, color image, visible range), 3D data, and expert evaluation data are used.

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Evgenii Semenishchev, Marina Zhdanova, Aleksandr Zelensky, Inessa Gracheva, Daniil Lyakhov, Nikita Mitugov, and Viacheslav Voronin "Formation of an algorithm for determining the degree of human involvement based on the analysis of the movement of the pupils of the operator and data on the position of the head and body", Proc. SPIE 12528, Real-Time Image Processing and Deep Learning 2023, 125280F (13 June 2023); https://doi.org/10.1117/12.2666763

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