Hand Gesture Recognition using Machine Learning Algorithms
Abhishek B1, Kanya Krishi2, Meghana M3, Mohammed Daaniyaal4, Anupama H S5
1Abhishek B, Department of Computer Science Engineering, BMSIT, Bangalore, India.
2Kanya Krishi, Department of Computer Science Engineering, BMSIT, Bangalore, India.
3Meghana M, Department of Computer Science Engineering, BMSIT, Bangalore, India.
4Mohammed Daaniyaal, Department of Computer Science Engineering, BMSIT, Bangalore, India.
5Anupama H S, Department of Computer Science Engineering, BMSIT, Bangalore, India.
Manuscript received on 14 April 2019 | Revised Manuscript received on 19 May 2019 | Manuscript published on 30 May 2019 | PP: 1734-1737 | Volume-8 Issue-1, May 2019 | Retrieval Number: A1834058119/19©BEIESP
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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: Gesture recognition is an emerging topic in today’s technologies. The main focus of this is to recognize the human gestures using mathematical algorithms for human computer interaction. Only a few modes of Human-Computer Interaction exist, they are: through keyboard, mouse, touch screens etc. Each of these devices has their own limitations when it comes to adapting more versatile hardware in computers. Gesture recognition is one of the essential techniques to build user-friendly interfaces. Usually gestures can be originated from any bodily motion or state, but commonly originate from the face or hand. Gesture recognition enables users to interact with the devices without physically touching them. This paper describes how hand gestures are trained to perform certain actions like switching pages, scrolling up or down in a page.
Index Terms: Gesture Recognition, Human Computer Interaction, User-Friendly Interface.
Scope of the Article: Human Computer Interactions