High-speed Integration of Kinect V2 Data for Identification of Hand Gesture in Real time Movements
1S.Chandra Sekhar,Ph.D. Scholar, Bapurao Deshmukh College of Engineering Sevagram Wardha, Maharashtra State, India.
2Dr. N.N. Mhala, Professor & Principal, Government Polytechnic College. Thane, Maharashtra State, India.
Manuscript received on November 10, 2019. | Revised Manuscript received on November 17, 2019. | Manuscript published on 30 November, 2019. | PP: 4010-4013 | Volume-8 Issue-4, November 2019. | Retrieval Number: K17420981119/2019©BEIESP | DOI: 10.35940/ijrte.K1742.118419
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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: Hand gesture recognition is extremely critical for human-PC connection. This manuscript presents a narrative constant strategy for human-hand gesture recognition. Here a framework for the discovery of quick gesture movement by utilizing a direct indicator of hand developments utilizing information combination technique. In our system, the hand area is removed from the foundation with the foundation subtraction strategy. At long last, the framework has been approved by methods for the Kinect v2 application actualized. The time requirement is recognized and the recognition is quick contrasted with other ongoing minutes. The timing analysis is compared , and the average time using data fusion method  is 63ms. By using fast integrating of data the average time is 45ms. The time taken for recognition of hand gesture is been improved. The experimental results are performed using Matlab tool.
Keywords: Gesture Recognition, Human Computer Interaction, Kinect V2 system
Scope of the Article: Human Computer Interaction (HCI).