Vision-Based Hand Gesture Recognition Techniques using Smartphones
Sachin Devangan1, Omkar Joshi2, Shanu Jaiswal3, Apratim Gholap4, Netra Lokhande5
1Sachin Devangan, Department of Information Technology, MIT College of Engineering Pune, India.
2Omkar Joshi, Department of Information Technology, MIT World Peace University, Kothrud, Pune, India.
3Shanu Jaiswal, Department of Information Technology, MIT World Peace University, Kothrud, Pune, India.
4Apratim Gholap, Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India.
5Dr. Netra Lokhande, Associate Professor, Department of Electrical Engineering, MIT World Peace University, Kothrud, Pune, India.
Manuscript received on June 08, 2020. | Revised Manuscript received on June 21, 2020. | Manuscript published on July 10, 2020. | PP: 85-90 | Volume-9 Issue-9, July 2020 | Retrieval Number: 100.1/ijitee.I6939079920 | DOI: 10.35940/ijitee.I6939.079920
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the past few years, the computational performance of smartphone devices has seen tremendous growth. Due to which the smartphone has become a suitable platform for various computer-vision based applications which earlier was not possible. In this paper, we study various methods through which we can achieve computer vision-based hand gesture recognition natively on smartphones. If smartphones can support hand gesture recognition it can provide a new way to interact with mobile devices and overcome the hurdles of voice and touch-based user interface improving the user experience at the same time also supports other gesture-based applications. The techniques we study are mainly vision-based since camera module is present on most of the smartphones and it does not require other additional sensors or other hardware. We have compared the various methods available based on algorithms used and corresponding accuracy.
Keywords: Hand gestures, Hand Gesture Recognition (HGR), Smartphone, Interface, User experience, Sign Language.
Scope of the Article: Pattern Recognition