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ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 6. Vol. 30. 2024
DOI: 10.17587/it.30.300-306
K . Sh . Gurbanova, Chief Specialist,
Training-Innovation Centre, Institute of Information Technology of The Ministry of Science and Education of the Azerbaijan Republic, Baku, Azerbaijan
Overview of Gesture Control Technologies
The dynamic development and rapid updating of information and communication technologies (ICT) has created a suitable environment for gesture control of modern computer and robot systems. It is noted that gestures are a necessary component in the communication process. At the same time, it is possible to control the equipment without contact with the support of methods that allow to select and recognize hand gestures. Sufficient work has been done and achievements have been made in the direction of automation and gesture control of technology. The study notes that such systems are more flexible and can easily adapt to people's changing needs. Building a human-machine interface speeds up the communication process and expands the user's capabilities. Gesture control technologies for computer and robotic systems have great potential. A comparative analysis of the parameters of gesture-controlled technologies is shown in the table.
Keywords: sign language, intelligent control systems, human-machine interface, robotics, smart home, gesture control technologies
P. 300-306
References
- Mahmudova R. Sh., Gurbanova K. Sh. The opportunities of technologies application of automatic recognition of gestures shown by the movement of hands, Problems of Information Technology journal, 2020, no. 2, pp. 102—110.
- Farooq U., MohdRahim S., Abid A. A multi-stack RNN-based neural machine translation model for English to Pakistan sign language translation, Neural Computing and Applications, 2023, pp. 1—14.
- Mahmudova R. Sh., Gurbanova K. Sh. Azerbaijani sign language and problems of its automatic recognition, National scientific-practical conference "ICT problems of the Azerbaijani language, ICT problems of the Azerbaijani language" dedicated to the 100th anniversary of the national leader Heydar Aliyev and the International Mother Language Day, Baku, Institute of Information Technologies, 21 February 22, 2023, pp. 105—112.
- Ryumin D. A., Kagirov I. A. Approaches to automatic recognition of gesture information: hardware and methods, Manned flights into space, 2021, no. 3, pp. 40.
- Gesture recognition technologies, available at: https://developers.sber.ru/help/ar-vr/gesture-recognition-technologies (access date: 10/16/2023).
- Technologies for controlling devices with gaze and gestures, available at: https://fotokomok.ru/texnologii-upravleniya-ustrojstvami-vzglyadom-i-zhestami/, (access date: 10/16/2023).
- Chistyakov I. S., Chepin E. V. Gesture recognition system based on Convolutional neural networks, IOP Conference Series. Materials Science and Engineering, 2019, vol. 498, no. 1, pp. 1—7.
- Budik A. nTobeBox: the first TV set-top box controlled by gestures, available at: http://mediapure.ru/onlajn-servisy/chto-takoe-stb-set-top-box-iptv-pristavka-ili-resiver-cifrovogo-televideniya/ (access date: 21/07/2023). https://3dnews.ru/635468 (access date: 03/08/2023).
- Sivak T. A., Kvasha P. Yu. Integration of tracking sensor technology into information modeling of buildings and structures, Construction: science and education, 2019, no. 4, pp. 1—1.
- Zheng W. Human grasp mechanism understanding, human-inspired grasp control and robotic grasping planning for agricultural robots, Sensors, 2022, vol. 22, no. 14, pp. 5240.
- Izountar Y. VR-PEER: A personalized exer-game platform based on emotion recognition, Electronics, 2022, vol. 11, no. 3, pp. 455.
- Putra H. G. P. Designing Machine Learning Model for Predictive Maintenance of Railway Vehicle, 2021 International Conference on ICT for Smart Society (ICISS) IEEE, 2—4 August 2021, pp. 1—5.
- Booker D. A. The future of fashion & human gesture control: exploration of a wearable communication device for sign language speakers, Massachusetts Institute of Technology, 2020, 75 p.
- Chao F. Use of automatic Chinese character decomposition and human gestures for Chinese calligraphy robots, IEEE Transactions on Human-Machine Systems, 2018, vol. 49, no. 1, pp. 47—58.
- Shakirov R. I., Artemov M. D., Voronova L. I. Data preparation subsystem for the software and hardware complex for sign language recognition, Telecommunications and Information Technologies, 2021, vol. 8, no. 2, pp. 101.
- Challenor J., White D., Murphy D. Hand-Controlled User Interfacing for Head-Mounted Augmented Reality Learning Environments, Multimodal Technologies and Interaction, 2023, vol. 7, no. 6, pp. 55.
- Heinrich A. Gest glove has gesture control on hand, available at: https://newatlas.com/gest-gesture-controller-glove/40174/(date of access: 27/07/2023).
- Varghese R. Automatic Voice Synthesis System using Long Short-Term Memory and Google Mediapipe, 12th International Conference on Computing Communication and Networking Technologies (ICCCNT) IEEE, 6-8 July 2021, pp. 1—5.
- Yu C. End-Side Gesture Recognition Method for UAV Control, IEEE Sensors Journal, 2022, vol. 22, no. 24, pp. 24526—24540.
- Freitas M. L. B. Surgical Instrument Signaling Gesture Recognition Using Surface Electromyography Signals, Sensors, 2023, vol. 23, no. 13, pp. 6233.
- Kavitha B. C. Mid-Air Gesture for Hand Control System Using Leap Motion Robot, Information and Communication Technology for Competitive Strategies (ICTCS 2022) Intelligent Strategies for ICT, Singapore, Springer Nature Singapore, 2023, pp. 259—265.
- Gurbanova K. Sh. Research of Stages, Types of Modeling and Methods of Gesture Recognition, Informacionnye Tehnologii, 2024, vol. 30, no. 2, pp. 85—90.
- Kataev M. Yu., Shirokov L. V. Methodology for determining hand gestures, Reports of the Tomsk State University of Control Systems and Radioelectronics, March 2013, no. 1 (27), pp. 45—49.
- Ovcharova B. S., Barashko E. N. Technologies for using gestures to control computer and robotic systems, Forum of young scientists, 2018, no. 12-3(28), pp. 578—584.
- Karpov A. A., Yusupov R. M. Multimodal interfaces of human-machine interaction, Bulletin of the Russian Academy of Sciences, 2018, vol. 88, no. 2, pp. 146—155.
- Akimov A. A., Mustafina S. A. Review of modern artificial intelligence methods for recognizing deviant behavior of an individual, Bulletin of the Technological University, 2020, vol. 23, no. 8, pp. 69—79.
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