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Control of adaptive running platform based on machine vision technologies and neural networks

  • 25-03-2022
  • Original Article
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Abstract

The article delves into the challenges and solutions for realistic movement in virtual reality, focusing on adaptive running platforms. It analyzes existing control methods and positioning techniques, highlighting the advantages of machine vision and neural networks. The study compares linear, nonlinear, and neural network control functions, demonstrating the effectiveness of specific methods for different positioning systems. The research includes experimental comparisons, revealing the best-performing functions for both tracker-based and machine vision-based positioning. The findings offer practical insights for improving the control of running platforms, contributing to enhanced user experience in virtual reality applications.

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Title
Control of adaptive running platform based on machine vision technologies and neural networks
Authors
Artem D. Obukhov
Mikhail N. Krasnyanskiy
Denis L. Dedov
Victoria V. Vostrikova
Daniil V. Teselkin
Ekaterina O. Surkova
Publication date
25-03-2022
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 15/2022
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-022-07166-9
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