An Analytical Study on Gesture Recognition Technology

  • Poorvika Singh Negi
  • Praveen KumarEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1090)


Over the years, mankind has adapted and evolved, opening up new horizons in terms technology. The intellect and inventiveness of human beings have led to the development of many tools, gesture recognition technology being one of them, to help extend the capabilities of our sense, combining natural gestures to operate technology and making the optimum use of our body gestures, decreasing human effort and going beyond human abilities. Devices these days usually have one type of sensor installed in them; however, this paper will be covering the effect of multiple sensors on recognition accuracy. Furthermore, this paper proposes a new tool for communication made by combining the British sign language with gesture-based technology, which can quickly translate sign language into text, with one mobile phone. Principles of generating EOG, methods of sampling EOG signals, basic eye modes, blinking and fixation modes.


Accelerometer British sign language (BSL) Human–computer interaction (HCI) Non-hearing-impaired (NHI) Sensors 


  1. 1.
    Murao, Kazuya, Tsutomu Terada, Ai Yano, and Ryuichi Matsukura. 2011. Evaluating Gesture Recognition by Multiple-Sensor-Containing Mobile Devices. In 15th Annual International Symposium on Wearable Computers, San Francisco, USA.Google Scholar
  2. 2.
    Lai, Ching-Hao. 2011. A Fast Gesture Recognition Scheme for Real-Time Human-Machine Interaction Systems. In Conference on Technologies and Applications of Artificial Intelligence.Google Scholar
  3. 3.
    Zabidi, Nur Syabila, Noris Mohd Norowi, and Rahmita Wirza O.K. Rahmat. 2016. A Review on Gesture Recognition Technology in Children’s Interactive Storybook. In 4th International Conference on User Science and Engineering (i-USEr).Google Scholar
  4. 4.
    Xue, Haoyun, and Shengfeng Qin. 2011. Mobile Motion Gesture Design for Deaf People. In Proceedings of the 17th International Conference on Automation & Computing. Huddersfield, 10, Sept 2011, UK: University of Huddersfield.Google Scholar
  5. 5.
    Rawat, Seema, Parv Gupta, and Praveen Kumar. 2014. Digital life assistant using automated speech recognition. In 2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), 43–47, IEEE.Google Scholar
  6. 6.
    Geer, D. 2004. Will Gesture Recognition Technology Point the Way. Computer 37 (10): 20–23. Los Alamitos, CA, USA.CrossRefGoogle Scholar
  7. 7.
    Sonkusare, J.S., Nilkanth. B. Chopade, Ravindra Sor, Sunil L. Tade. 2015. A Review on Hand Gesture Recognition System. In International Conference on Computing Communication Control and Automation.Google Scholar
  8. 8.
    Murao, Kazuya, Ai Yano, Tsutomu Terada, Ryuichi Matsukura. 2012. Evaluation Study on Sensor Placement and Gesture Selection for Mobile Devices. In Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia, New York, USA.Google Scholar
  9. 9.
    Konwar, P., H. Bordoloi. 2015. An EOG Signal Based Framework to Control a Wheel Chair. USA: IGI Global.Google Scholar
  10. 10.
    Wenhui, Wang, Chen Xiang, Wang Kongqiao, Zhang Xu, and Yang Jihai. 2009. Dynamic Gesture Recognition based on Multiple Sensors Fusion Technology. In 31st Annual International Conference of the IEEE EMBS, 2–6, Sept, Minneapolis, Minnesota, USA.Google Scholar
  11. 11.
    Kumar, Praveen, Bhawna Dhruv, Seema Rawat, and Vijay S. Rathore. 2014. Present and future access methodologies of big data. International Journal of Advance Research In Science and Engineering 3: 541–547. 8354.Google Scholar
  12. 12.
    Kumar, Manish, Mohd Rayyan, Praveen Kumar, and Seema Rawat. 2016. Design and development of a cloud based news sharing mobile application. In 2016 Second International Innovative Applications of Computational Intelligence on Power, Energy and Controls with their Impact on Humanity (CIPECH), 217–221, IEEE.Google Scholar
  13. 13.
    Saeed, Atif, Muhamamd Shahid Bhatti, Muhammad Ajmal, Adil Waseem, Arsalan Akbar, and Adnan Mahmood. 2013. Android, GIS and Web Base Project, Emergency Management System (EMS) Which Overcomes Quick Emergency Response Challenges. In Advances in Intelligent Systems and Computing, vol 206, Springer: Berlin.Google Scholar
  14. 14.
    Chaturvedi, Anshika, Praveen Kumar, and Seema Rawat. 2016. Proposed noval security system based on passive infrared sensor. In International Conference on Information Technology (InCITe)-The Next Generation IT Summit on the Theme-Internet of Things: Connect your Worlds, 44–47, IEEE.Google Scholar
  15. 15.
    Lin, Min, Guoming Mo. 2011. Eye gestures recognition technology in Human-computer Interaction. In 4th International Conference on Biomedical Engineering and Informatics (BMEI), Shanghai, China.Google Scholar
  16. 16.
    Phade, G.M., P.D. Uddharwar, P.A. Dhulekar, and S.T. Gandhe. 2014. “Motion Estimation For Human–Machine Interaction. International Symposium on Signal Processing and Information Technology (ISSPIT).Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Amity University Uttar PradeshNoidaIndia

Personalised recommendations